Method and system for passive electroseismic surveying

ABSTRACT

A method of passive surveying comprises generating one or more detected signals by passively detecting a signal generated within a subsurface earth formation due to a seismoelectric response or an electroseismic response in at least one porous subsurface earth formation containing at least one fluid, and processing the one or more detected signals to determine at least one property of the subsurface earth formation.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.13/674,584 filed Nov. 12, 2012 and entitled “Method and System forPassive Electroseismic Surveying” which is a continuation of U.S.application Ser. No. 13/431,735 filed Mar. 27, 2012 and entitled “Methodand System for Passive Electroseismic Surveying” which claims priorityunder 35 U.S.C. §119 of provisional application No. 61/469,498 filedMar. 30, 2011 entitled “Method and System for Passive ElectroseismicSurveying” and provisional application No. 61/528,421 filed Aug. 29,2011 and entitled “Passive Electromagnetic Tool for Direct HydrocarbonIndication”.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

REFERENCE TO A MICROFICHE APPENDIX

Not applicable.

BACKGROUND

Conventional geophysical surveying techniques employ several distincttechnologies, which can include seismology, controlled-sourceelectromagnetics, (CSEM), magnetotellurics, microseismology, gravity,magnetics, and controlled source electroseismology and seismoelectricsurveying. Gravity and magnetics technologies survey large areas, suchas whole geological basins. These technologies generally identifyprospective regions with attractive geological features but do notgenerally identify the detailed location of hydrocarbon reservoirs ormineral resources. Microseismology generally relies on small, localizedseismic events generated in the earth by naturally occurring earthmovements or by well-drilling operations. Microseismology may locate thesource of fracturing events such as encountered in fracturingreservoirs. Magnetotellurics uses the low-frequency portion of theearth's background electromagnetic fields to estimate the subsurfaceelectrical conductivity but the method does not provide a detailedlocation or shape of target reservoir structures. Seismology producesinformation indicative of reservoir structures and CSEM provideselectrical resistivity information that indirectly indicates thepresence of hydrocarbons. Controlled source electroseismology andelectroseismic surveying use high-power seismic or electromagneticsources to create images of the subsurface that provide both structuraland fluid property information. These methods are seldom used becausethey are significantly limited by the requirement for high-powersources.

In gravity surveying, sensitive gravity detectors are placed on theearth or above the earth. Reservoirs typically have smaller mass densitythan non-reservoir rock. The sensitive gravity meter detects a minimumin local gravitational acceleration over a reservoir. Gravity studieshave several limitations. Local gravity values reflect an average of themass densities from all materials in the neighborhood of the sensor.Whereas reservoirs of low density reduce the measured gravitationalacceleration, the presence of high-density rock reduces the spatialresolution of the measurement and may obscure the presence of alow-density formation. The spatial resolution of gravity measurements islimited to length scales comparable to the depth and lateral extent ofthe reservoir. The amplitude of the identifying gravity signaturedepends on the volume of the reservoir. Little information is providedregarding the reservoir structure, pore-fluid properties, or thepermeability.

In magnetic surveying, magnetic-field sensing devices measure themagnetic field of the earth, typically from aircraft. Hydrocarbonreservoirs and mineral deposits, such as iron ore, may alter the localearth's magnetic field. Measured data can be used to indicate thepresence of reservoir structures. Magnetic surveying is limited becauseit measures neither properties related to the reservoir spatial extentand structure, nor the fluid identity and flow properties.

Seismic prospecting techniques generally involve the use of a seismicenergy source and a set of receivers spread out along or near theearth's surface to detect seismic signals reflected from subsurfacegeological boundaries. These signals are recorded as a function of time,and subsequent processing of these signals is designed to reconstruct anappropriate image of the subsurface formation. In generic terms, thisconventional process has seismic energy traveling down into the earth,reflecting from a particular geologic layer at a seismic impedancecontrast, and returning to the receiver as a reflected seismic wave.

The seismic energy may be so-called shear waves (S-waves) or so-calledcompressional waves (P-waves). Shear waves and compressional wavesdiffer with respect to their velocities, angles of reflection,vibrational directions, and to some extent the types of information thatmay be obtained from their respective types of seismic data. However,both types of waves suffer similar attenuation by earth formations; thatis, the earth formations tend to attenuate the higher frequencycomponents and allow the lower frequency components to pass through theearth relatively unattenuated. This means that, for deeper formations,the low frequency content of the reflected seismic energy contains theinformation about the underlying subsurface formations. However, becauseof the low frequency of the detected reflected seismic energy, theresolution of the reflected seismic energy may be insufficient to allowfor detection of very thin geologic layers.

Further, if the seismic impedance contrast between adjacent but distinctgeologic layers is small, little seismic energy is reflected and thedistinctness of the geologic layers may not be discernible from thedetected or recorded seismic data. Additionally, seismic studies mightprovide information about the structure of rock formations in thesubsurface but generally are not able to distinguish between porefluids, such as an aqueous fluid, oil, or gas.

Magnetotelluric surveying generally involves the use of the naturalelectromagnetic fields that originate in the earth's atmosphere.Naturally-occurring electromagnetic fields propagate into the subsurfacewhere they encounter rock formations of differing electricalconductivity. When the electromagnetic fields contact a formation of lowconductivity, such as is typical of hydrocarbon reservoirs, theelectromagnetic field measured at the surface of the earth changes.Spatially-dependent electromagnetic fields measured on the earth'ssurface can be used to indicate the presence of low-conductivityformations that might contain hydrocarbons. Magnetotelluric surveyinghas several limitations. Only low-frequency, long-wavelengthelectromagnetic stimulation may reach prospective reservoirs because thehigh-frequency electromagnetic fields are rapidly attenuated by theconducting earth. Long-wavelength electromagnetic waves limit thespatial resolution of magnetotellurics making reservoir delineationdifficult. Additionally, magnetotelluric surveying only providesinformation about formation electrical conductivity and does not yielddata revealing information about porosity, permeability, or reservoirstructure.

Seismic energy may be so-called micro-seismic energy. Seismic waves aregenerated in the earth by tectonic forces, by ocean tides and othernatural phenomena. Seismic waves are also created when drilling or earthfracturing operations are conducted in hydrocarbon exploration,production, or in water well services. The events created by thesenatural and man-made events are called microseismic events. Generally,micro-seismic studies yield qualitative information about the locationof subsurface structures or positional information about drillingoperations. In these studies the location of the seismic source isimperfectly known so that only poor quality images of the subsurface arepossible.

Controlled-source electromagnetic surveying involves the use of a sourceof electrical power and a set of electromagnetic receivers typicallydeployed on the seafloor in deep water. Although CSEM surveying may bedone on land or in shallow water, recent work finds particularly usefulapplications in deep water. In CSEM surveying, the power source drivesan electrical current into the earth that passes through the varioussubsurface rock formations. The electrical current follows a path of lowelectrical resistance through the most conducting rock masses.Hydrocarbon reservoirs contain insulating gas or oil fluids so theapplied electrical current tends to flow around the resistive reservoirstructures. The deflection of current around reservoirs is detected as achange in electromagnetic response on the detectors deployed on theseafloor. The measured signal properties can be used to reflect thepresence of resistive reservoir structures.

SUMMARY

In an embodiment, a method of passive surveying comprises generating oneor more detected signals by passively detecting a signal generatedwithin a subsurface earth formation due to a seismoelectric response oran electroseismic response in at least one porous subsurface earthformation containing at least one fluid, and processing the one or moredetected signals to determine at least one property of the subsurfaceearth formation. Generating the one or more detected signals maycomprise generating a detected electromagnetic field by detectingearth's electromagnetic field using an electromagnetic field detectorand processing the one or more detected signals may comprisesdemodulating a portion of the signal to identify an envelope of thesignal, wherein the envelope is indicative of the presence of thehydrocarbons. Processing the one or more detected signals may alsocomprise analyzing the envelope to determine a value correlated to adepth of the hydrocarbons in the subterranean formation. Demodulatingthe portion of the signal may comprise extracting a frequencymodulation, a phase modulation, an amplitude modulation, or anycombination thereof from the signal. The envelope may comprise at leastone of the frequency modulation, the phase modulation, or the amplitudemodulation. Generating the one or more detected signals may comprisegenerating a detected electromagnetic field by detecting earth'selectromagnetic field using an electromagnetic field detector, andprocessing the one or more detected signals may comprise processing thedetected electromagnetic field to determine the at least one property ofthe subsurface earth formation. Generating the one or more detectedsignals may comprise generating a detected seismic signal by detecting aseismic wave generated within the subsurface earth formation using aseismic sensor, and processing the one or more detected signals maycomprise processing the detected seismic signal to determine the atleast one property of the subsurface earth formation. In anotherembodiment, generating the one or more detected signals may comprisegenerating a detected electromagnetic field by detecting earth'selectromagnetic field using an electromagnetic field detector, andgenerating a detected seismic signal by detecting a seismic wave using aseismic sensor. Processing the one or more detected signals may compriseprocessing the detected electromagnetic field and the detected seismicsignal to determine the at least one property of the subsurface earthformation. The detected electromagnetic field may be generated at adifferent time than the detected seismic signal. The detectedelectromagnetic field may be generated at a different location than thedetected seismic signal. The at least one fluid may comprise at leastone component selected from the group consisting of: an aqueous fluid, ahydrocarbon, a petroleum, carbon dioxide, and any combination thereof.

In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises one or more sensors coupled to aprocessor that detect one or more signals generated within a subsurfaceearth formation due to a seismoelectric response or an electroseismicresponse in at least one porous subsurface earth formation containing atleast one fluid, and an analysis tool, that when executed on theprocessor, configures the processor to receive the one or more signalsfrom the one or more sensors, and process at least a portion of the oneor more signals to determine at least one property of the subsurfaceearth formation. The one or more sensors may comprise one or moreelectromagnetic field detectors that measures the earth'selectromagnetic field and produces a signal indicative of the detectedelectromagnetic field, and the analysis tool may configures theprocessor to receive the signal from the one or more sensors, demodulatea portion of the signal to identify an envelope of the signal, analyzethe envelope to determine one or more properties indicative of thepresence of the hydrocarbons, and analyze the envelope to determine thedepth of the hydrocarbons in the subterranean formation. The one or moresensors may comprise an electromagnetic field detector that measures theearth's electromagnetic field and produces a signal indicative of thedetected electromagnetic field, and the analysis tool may receive thesignal and determine the at least one property of a subsurface earthformation. The one or more sensors may comprise a seismic sensor thatdetects a seismic signal related to earth's electromagnetic field andproduces a first signal indicative of the detected seismic signal, andthe analysis tool may receive the first signal and process the firstsignal to determine the at least one property of the subsurface earthformation. The one or more sensors may comprise a seismic sensor thatdetects a seismic signal related to earth's electromagnetic field andproduces a first signal indicative of the detected seismic signal and anelectromagnetic field detector that measures the earth's electromagneticfield and produces a second signal indicative of the detectedelectromagnetic field. The analysis tool may receive the first signaland the second signal and determine the at least one property of asubsurface earth formation. The first signal may be generated at adifferent time than the second signal, and/or the first signal may begenerated at a different location than the second signal. Theelectromagnetic field detector may comprise a plurality of pairs ofporous pot electrodes, and each pair of porous pot electrodes may beelectrically coupled. The electromagnetic field detector may comprise aplurality of pairs of conductive electrodes, and each pair of conductiveelectrodes may be electrically coupled. The electromagnetic fielddetector may comprise a conductive electrode coupled to a porous potelectrode. The electromagnetic field detector may comprise an antennadisposed on or above the surface of the earth. The antenna may compriseat least one antenna selected from the group consisting of: aparallel-plate capacitor antenna comprising two or more parallelconducting plates, a single-plate capacitor antenna comprising oneelectrode electrically coupled to the earth, a monopole antennacomprising a conducting element, a dipole antenna comprising twoconducting elements, a multi-pole antenna comprising a plurality ofconducting elements, a directional antenna comprising conductingelements arranged to augment a signal amplitude in a particulardirection, a coil antenna comprising one or more coils of wire, aconcentric electric dipole, and any combination thereof. The seismicsensor may comprise at least one sensor selected from the groupconsisting of: a hydrophone, a single-component geophone, atwo-component geophone, a three-component geophone, a single-axisaccelerometer, a two-axis accelerometer, a three-axis accelerometer, andany combination thereof.

In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: a memory comprising a non-transitorycomputer readable media, a processor, and an analysis tool, that whenexecuted on the processor, configures the processor to: receive one ormore signals from one or more sensors, wherein the one or more sensorsdetect one or more signals generated within a subsurface earth formationdue to a seismoelectric response or an electroseismic response in atleast one porous subsurface earth formation containing at least onefluid, and process at least a portion of the one or more signals todetermine at least one property of the subsurface earth formation. Theone or more sensors may comprise one or more electromagnetic fielddetectors that measure the earth's electromagnetic field and produce asignal indicative of the detected electromagnetic field. The analysistool may also configure the processor to: receive the signal from theone or more electromagnetic field detectors; demodulate a portion of thesignal to identify an envelope of the signal; analyze the envelope todetermine one or more properties indicative of the presence of thehydrocarbons; and analyze the envelope to determine the depth of thehydrocarbons in the subterranean formation. The one or more sensors maycomprise an electromagnetic field detector that measures the earth'selectromagnetic field and produces a signal indicative of the detectedelectromagnetic field, and the analysis tool may configure the processorto receive the signal and determine the at least one property of asubsurface earth formation. The one or more sensors may comprise aplurality of seismic sensors that detect a seismic signal related toearth's electromagnetic field and produce a first signal indicative ofthe detected seismic signal. The analysis tool may configure theprocessor to receive the first signal, and process the first signal todetermine the at least one property of the subsurface earth formation.The one or more sensors may comprise a plurality of seismic sensors thatdetect a seismic signal related to earth's electromagnetic field andproduce a first signal indicative of the detected seismic signal and anelectromagnetic field detector that measures the earth's electromagneticfield and produces a second signal indicative of the detectedelectromagnetic field. The analysis tool may also configure theprocessor to receive the first signal and the second signal anddetermine the at least one property of a subsurface earth formation. Theone or more sensors may comprise a seismic sensor that detects a seismicsignal related to earth's electromagnetic field and produces a firstsignal indicative of the detected seismic signal, and an electromagneticfield detector that measures the earth's electromagnetic field andproduces a second signal indicative of the detected electromagneticfield. The analysis tool configures the processor to receive the firstsignal and the second signal and determines the at least one property ofa subsurface earth formation.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the features and advantages of thepresent invention, reference is now made to the detailed description ofthe invention along with the accompanying figures in which correspondingnumerals in the different figures refer to corresponding parts and inwhich:

FIG. 1 is a cross-sectional view of a passive surveying system accordingto an embodiment.

FIG. 2 is a cross-sectional view of a porous subsurface earth formationcontaining at least one fluid according to an embodiment.

FIG. 3 is a cross-sectional view of a passive surveying system accordingto an embodiment.

FIG. 4 is a perspective view of a passive surveying system according toan embodiment.

FIG. 5 is a perspective view of a passive surveying system according toembodiment.

FIG. 6 is another cross-sectional view of a passive surveying systemaccording to an embodiment.

FIG. 7 is still another cross-sectional view of a passive surveyingsystem according to an embodiment.

FIG. 8 is another perspective view of a passive surveying systemaccording to an embodiment.

FIG. 9 is a schematic view of a computer useful with an embodiment.

FIG. 10 illustrates passive seismoelectric test results using anembodiment of the system and methods disclosed herein.

FIG. 11 illustrates passive electroseismic test results using anembodiment of the system and methods disclosed herein.

FIG. 12 illustrates combined passive electroseismic and seismoelectrictest results using an embodiment of the system and methods disclosedherein.

FIG. 13 illustrates another passive seismoelectric test results using anembodiment of the system and methods disclosed herein.

DETAILED DESCRIPTION

It should be understood at the outset that although illustrativeimplementations of one or more embodiments are illustrated below, thedisclosed systems and methods may be implemented using any number oftechniques, whether currently known or not yet in existence. Thedisclosure should in no way be limited to the illustrativeimplementations, drawings, and techniques illustrated below, but may bemodified within the scope of the appended claims along with their fullscope of equivalents.

Overview

In controlled-source seismoelectric surveying, generally a seismicsource that might be dynamite or a seismic vibrator, creates a seismicwave that propagates into the subsurface where its seismic energy ispartially converted to an electric field at a boundary between rocktypes or at fluid interfaces. The produced electric field thenpropagates to the surface of the earth where it is detected withelectric and/or magnetic field sensors. In controlled-sourceelectroseismic surveying, a source of electrical power is connected toelectrodes in contact with the earth's surface. The voltage applied tothe electrodes causes electrical current to flow in the subsurface. Whenthat current passes through a rock boundary or a fluid interface, aportion of the electrical energy is converted to seismic energy. Theresulting seismic energy propagates to the earth's surface where it isdetected with seismic detectors that might be selected from geophones,accelerometers, or hydrophones. Both seismoelectric and electroseismicconversion amplitudes depend on the presence of hydrocarbon fluids soboth methods yield information about rock fluid content that is of usein hydrocarbon exploration and production. Both methods also yield highresolution images of rock formations that are typical of seismicsurveying. However, the high power sources that are required in thesemethods limit their usefulness.

The systems and methods disclosed herein utilize naturally occurringelectromagnetic fields (e.g., the earth's background electromagneticfield) and their interactions with a subsurface formation throughelectroseismic and/or seismoelectric conversions to employ passivesurveying. Previous surveying methods differ from the methods andsystems described herein in several ways. Some novel elements of thepresent methods and systems include: the creation of seismic waves in apassive measurement where the source is the earth's electromagneticfield; the subsequent conversion of that seismic energy toelectromagnetic energy; the detection of the generated seismic energyand/or detection of the further conversion of the seismic energy toelectromagnetic energy; identifying the generated seismic energy bydetecting the characteristic time lags or frequencies associated withthe seismic travel time using a frequency-selective method; anddetermining the depth of origin of the seismic signal from saidfrequency selective method.

As described in more detail herein, passive surveying may involvedetecting a seismic and/or electromagnetic signal generated in asubterranean formation, and processing the resulting signal to determinethe presence of one or more fluids (e.g., a hydrocarbon, an aqueousfluid such as potable water, fresh water, brine, etc.) in thesubterranean formation. The one or more signals may be detected using avariety of sensors and systems as described below. The detection mayinvolve 1) detecting an electromagnetic signal alone, 2) detecting aseismic signal alone, 3) detecting both an electromagnetic signal and aseismic signal at different times and/or locations, and/or 4) detectingboth an electromagnetic signal and a seismic signal at overlapping timeintervals to allow for cross correlation of the two detected signals.The detected signals may then be processed using a variety of techniquesto determine if one or more fluids are present in a subterraneanformation, and optionally one or more additional properties of the oneor more fluids in the subterranean formation (e.g., an existence of asubsurface earth formation containing at least one fluid, a depth of thesubsurface formation, a porosity, a fluid permeability, a composition ofat least one fluid within the subsurface earth formation, a spatialextent of the subsurface earth formation, an orientation of theboundaries of the subsurface earth formation, a resistivity, and anycombination thereof).

Each of these surveying techniques described herein can utilize apassive source to provide the energy for generating the electroseismicand/or seismoelectric conversions. As used herein, a “passive source”includes any source that is not being actively used to generate aseismic and/or electromagnetic signal for use with surveying asubterranean formation. The passive source generally comprises a naturalsource of electromagnetic energy such as the earth's naturalelectromagnetic field, though other man-made source of electromagneticradiation such as electrical power lines may also be included. Whilecertain man-made sources may induce an electromagnetic field, they aredistinguishable from an “active source” (e.g., a seismic generator,explosives, electric field generators, etc.) in that they are generallystationary, not used for surveying a subterranean formation, and/or notassociated with the detectors being used to detect the seismic and/orelectromagnetic signal. As used herein, “passive surveying,” “passiveelectroseismic surveying,” and “passive seismoelectric surveying” maythen utilize a passive source (e.g., the earth's natural electromagneticfield as the source field). The passive surveying can then make use ofthe generation of secondary seismic waves through coupling of theelectromagnetic source field to various rock formations (electroseismiceffect) and subsequent generations of secondary electromagnetic fieldsthrough coupling of the generated seismic waves with various rockformations (seismoelectric effect) to probe those formations and thefluids they contain. Generation of tertiary and higher orderelectromagnetic fields and seismic waves can also result from additionalcouplings.

Having generally described the systems and methods for passivesurveying, the detection systems, signals, and processing techniqueswill now be described in more detail.

Electroseismic and Seismoelectric Conversions

The systems and methods disclosed herein advantageously utilize signalsthat have heretofore been neglected and/or not detected. Magnetotelluricsurveying generally involves the use of the natural electromagneticfields that originate in the earth's atmosphere. In magnetotelluricsurveying, naturally-occurring electromagnetic fields propagate into thesubsurface where they encounter rock formations of differing electricalconductivity. When the electromagnetic fields contact a formation of lowconductivity, such as is typical of hydrocarbon reservoirs, theelectromagnetic field measured at the surface of the earth changes.Spatially-dependent electromagnetic fields measured on the earth'ssurface can be used to indicate the presence of low-conductivityformations that might contain hydrocarbons. Magnetotelluric surveyinghas several limitations. Only low-frequency, long-wavelengthelectromagnetic stimulation may reach prospective reservoirs because thehigh-frequency electromagnetic fields are rapidly attenuated by theconducting earth. Long-wavelength electromagnetic waves limit thespatial resolution of magnetotellurics making reservoir delineationdifficult. Additionally, magnetotelluric surveying only providesinformation about formation electrical conductivity and does not yielddata revealing information about porosity, permeability, or reservoirstructure.

In contrast to the magnetotelluric surveying method, the passiveelectroseismic surveying method makes explicit use of the generation ofseismic waves through the electroseismic effect, and the subsequentgeneration of secondary electromagnetic fields and seismic waves throughcombinations of the electroseismic and seismoelectric effects todetermine one or more properties of a subsurface earth formation ofinterest that cannot be learned from the magnetotelluric surveyingmethod. In addition, the passive electroseismic surveying methodaddresses the spatial resolution issue of the magnetotellurics surveyingmethod. Similarly, the seismic signals generated due to the interactionsbetween the electromagnetic field and the subterranean formation may beused alone or in combination with the electromagnetic field measurementsto determine one or more properties of the subsurface earth formation.

An understanding of the electroseismic and seismoelectric effects usefulin passive surveying begins with an understanding of the electromagneticfield within the earth, at least a portion of which may comprise thenaturally occurring background electromagnetic field of the earth. Theearth's naturally occurring electromagnetic field comprises a broadspectrum of frequencies, from sub-hertz frequencies to tens of thousandsof hertz frequencies, having a broad coverage over the surface of theearth. This broad spectrum allows for a broad range of penetrationdepths from tens of meters to tens of kilometers. The variousfrequencies in the earth may result from various natural events such aselectromagnetic fluctuations in the ionosphere and/or naturallyoccurring electromagnetic discharges in the atmosphere (e.g.,lightning). Further information concerning the earth's backgroundelectromagnetic field including the sources of the earth'selectromagnetic field and the power and frequency spectrum associatedwith the earth's electromagnetic field can be found in PRACTICALMAGNETOTELLURICS by Simpson et al., published by Cambridge UniversityPress (2005), which is incorporated by reference herein in its entirety.Other sources of electromagnetic radiation may include cultural sourcesof electromagnetic radiation that may contain electromagnetic radiationwith sufficiently low frequencies to reach and interact with asubterranean formation. Power transmission lines are one example of acultural source of electromagnetic radiation that can interact with asubterranean formation.

The earth's electromagnetic field propagates as an electromagneticmodulation that unlike an acoustic wave travels at the speed of anelectromagnetic wave in the subsurface, which is less than the speed ofan electromagnetic wave in a vacuum or air. The electromagnetic wave maytypically travel in the subsurface of the earth at a speed of about onehundred times greater than the speed of propagation of an acoustic wavein the seismic frequency band of about 1-100 Hz. Due to the relativespeed of the electromagnetic wave when compared to the seismic signal,the travel time of the electromagnetic wave into the subsurface earthformation is generally neglected for purpose of processing the detectedelectromagnetic field and/or the detected seismic signal in the methodsdisclosed herein.

As shown in FIG. 1, the earth's electromagnetic field 106 may encounterfluid dipoles 114 associated with at least one fluid in a porous earthformation layer. A portion 116 of this formation layer is depicted in anexploded view in FIG. 1. In general, the earth's electromagnetic field106 causes a change in the polarization of the dipoles 114 in the porefluid, which in turn causes the fluid to flow or to generate a pressurepulse 118. The flowing fluid (or pulse) produces a time varying pressuregradient, which is then propagated into the earth formation (or rock).The pressure gradient then propagates through the subsurface to thesurface as a seismic wave 120. The term “seismic wave” is used herein tomean any mechanical wave that propagates in the subsurface of the earthand includes, but is not limited to, P- and S-waves.

In order to more clearly illustrate the basis for the passiveelectroseismic surveying system and method disclosed herein, theconversion of the earth's electromagnetic field to seismic energy in atleast one porous subsurface earth formation containing at least onefluid will be described in more detail with reference to FIG. 1 and FIG.2. The formations of interest may generally be porous, as is moreclearly illustrated in FIG. 2. A porous formation generally comprises asolid rock portion 201 interspersed throughout with channel-like porousspaces 202. The term “porous” is used herein to mean some earthsubstance containing non-earthen volume or pore space, and includes, butis not limited to, consolidated, poorly consolidated, or unconsolidatedearthen materials. Where a polarizable fluid (e.g., aqueous or otherpolarizable fluid) exists, an electrochemical interaction may formbetween the polarizable fluid and the solid rock portions 201. Thepolarizable fluid may include, but is not limited to, an aqueous fluid,hydrocarbons, petroleum, or any combinations thereof. Theelectrochemical interaction is represented by the “+” symbol in thefluid portion and the “−” symbol in the rock portion of the formation.In general, the rock portion 201 may have an existing natural surfacecharge over at least a portion of the rock surface. This electrochemicalinteraction may result in a local pore fluid dipole that causes a localbackground electromagnetic field. It may be noted that, overall, thereis no net dipole field in unperturbed rock and its associated fluids.The sign of the background electromagnetic field or field polaritydirection depends on the surface charge on the solid and the way thefluid screens out that charge. In clays, the charge is typically asshown in FIG. 2. However, in other materials (e.g., carbonates), thecharge could be reversed (i.e., with the “+” charge on the solid).

When the earth's electromagnetic field 122 interacts with the formation,as illustrated for a region of the formation, the backgroundelectromagnetic field that acts upon the established fluid dipole 114 orthe charges associated with that dipole changes, causing fluid movement.This is illustrated by the earth's electromagnetic field 106 shown inFIG. 1. Although the earth's electromagnetic field 106 may be a timevarying field, the earth's electromagnetic field 106 is illustrated as astatic electric field 122 in FIG. 2 for ease of discussion. Thiselectric field 122 has the effect of modifying the electrochemical bondsor moving the charges (depicted by the small arrows above and below the“charges” in the fluid in FIG. 2), thereby effectively creating apressure pulse where the interactions are distorted or broken. Thiselectric field 122 exists throughout the fluid area and primarilyaffects the charges of the dipoles 114 which are at or near the fluidsurface or interface of the rock. Thus, a pore fluid pressure pulse isgenerated from the resulting charge movement and this resulting pressurepulse is transmitted to the solid rock portions 201 of the formation. Inturn the pressure pulse is transmitted through the rock portions 201 asa seismic wave 120. This effect may be referred to as the electroseismiceffect or the electrokinetic effect. Thus, an appropriate subsurfaceformation layer may be a subsurface source of seismic energy. A moredetailed description of the electroseismic effect and the electrokineticeffect can be found in U.S. Pat. No. 5,877,995 entitled “GeophysicalProspecting” and issued to Thompson et al., and which is incorporatedherein by reference in its entirety. Additional information onseismoelectric surveying may be found in U.S. Pat. No. 4,904,942entitled “Electroseismic Prospecting by Detection of an ElectromagneticSignal Produced by Dipolar Movement” and issued to Thompson, which isincorporated herein by reference in its entirety.

Seismoelectric and electroseismic effects are also known to generateharmonic responses where the coupling of electromagnetic and seismicmodulations creates new modulations at frequencies that are harmonics ofthe generating seismic and electromagnetic signals. Nonlinearelectroseismic conversions may produce signals useful during processing.In an embodiment, nonlinear, harmonic signals having frequencycomponents at higher frequency harmonics of the source's fundamentalfrequency (i.e., those frequencies present in the earth's backgroundelectromagnetic field) may be detected as a result of distortions of thebackground electromagnetic field interacting with the subsurface earthformation containing at least one fluid. The harmonic signals may beprocessed alone or in conjunction with the fundamental frequencies ofthe detected seismic signal and/or the detected electromagnetic field todetermine one or more properties of the subsurface earth formation. Inan embodiment, the harmonic signals may be present, detected, and/orisolated in both the detected electromagnetic field and the detectedseismic signal. A detailed description of the nonlinear, harmonicgeneration of electroseismic and seismoelectric effects can be found inU.S. Patent Application Publication No. 2002/0181326 A1 entitled“Nonlinear Electroseismic Exploration” and is issued to Hornbostel etal., and which is incorporated herein by reference in its entirety.

A portion of this seismic energy generated by the conversion of theearth's electromagnetic field to seismic energy may travel upwardly fromthe formation (seismic wave 120) towards the surface, where it may bedetected by one or more seismic sensors, which may be arranged in anarray. When conventional seismic reflection boundaries exist between theformation and surface, seismic reflections may occur and may be detectedby the detector array, also in a conventional fashion. The detection ofthe resulting subsurface-generated seismic wave may occur whenever thereis fluid in a porous formation, including formations of lowpermeability.

With reference to FIGS. 2 and 3, a seismoelectric effect may also beobserved based on the same principles as the electroseismic effect.Rather than an electromagnetic wave interacting with the fluid in a poreto produce a seismic wave, a seismic wave that originated due to theelectroseismic effect, may interact with the fluid in a pore 202 nearthe surface of the earth to generate a modification of the chargespresent within the pore 202. This pore 202 could be filled with freshwater as is present in the water table. The resulting modification ofthe charges may generate an alternating current field, which may lead tothe emission of an electromagnetic signal 124. This electromagneticsignal may be directly detected by one or more electromagnetic sensors,which may be arranged in an array. In addition, the resultingtime-variant electromagnetic field resulting from the seismoelectriceffect may be referred to as a modulating signal since it may modulatean electromagnetic field within the earth (e.g., the near surface of theearth). As used herein, the term modulation can refer to frequencymodulation, phase modulation, and/or amplitude modulation. The seismicwave that originated due to the electroseismic effect may travel to thenear surface of the earth where it directly modulates an electromagneticfield within the earth (e.g. the near surface of the earth). Thismodulation is believed to occur because the passage of the seismic wavecauses a change in the electrical impedance that results in atime-dependent variation of the electromagnetic field and/or the passageof the seismic wave interacts with a fluid or rock boundary to producean electromagnetic field. The modulated signal may then be detectable inthe near surface or just above the surface of the earth. A portion ofthe electromagnetic field generated by the conversion of the seismicwaves to electromagnetic energy and/or the modulating signal generatedby the conversion of the seismic waves to electromagnetic energy or theseismic wave generated by the electroseismic effect may be detected byone or more sensors. The detection of the resulting subsurface generatedelectromagnetic signal, the modulating signal, and/or the seismic signalmay occur whenever there is fluid in a porous formation, includingformations of low permeability. The indication of a fluid in a porousformation may be used to locate or potentially locate a hydrocarbon in asubterranean formation and/or locate or potentially locate an aqueousfluid (e.g., fresh water, potable water, brine, etc.) in the earth(e.g., detecting water or the water level in a subsurface water table).

The earth's electromagnetic field may propagate into the subsurface ofthe earth as an approximate plane wave, including over a subsurfaceformation of interest. As used herein, a “plane wave” refers to a wavewith a substantially uniform amplitude on a plane normal to the velocityvector. The velocity vector may be generally vertical and may notnecessarily be perpendicular to the surface of the earth above thesubsurface formation of interest. For example, the velocity vector wouldbe approximately vertical rather than inclined from the vertical axiswhere the surface of the earth above a subsurface formation of interestwas inclined to the vertical (e.g., on a hill or slope). As a result ofthe electroseismic effect and/or seismoelectric effect, the seismicand/or electromagnetic waves resulting from the earth's electromagneticfield may be generated somewhat uniformly across the subsurfaceformation containing at least one fluid, resulting in a seismic and/orelectromagnetic wave that is approximately a plane wave traveling backto the surface of the earth. The discovery of this result may be usefulin processing the various detected signals, as described in more detailbelow.

Passive Electromagnetic Field Detection Systems

Various sensors and detection mechanisms may be used to detect theelectromagnetic field within and/or above the surface of the earth.Referring now to FIG. 3, a system 300 of geophysical surveying isillustrated in a simplified manner for the purpose of clarity. In system300, a sensor 126 for detecting an electromagnetic field 124 is disposedin contact with or near the surface of the earth 108. Theelectromagnetic field 124 may be emitted above the surface of the earth108 as a detectable electromagnetic field 128. It can be noted that theelectromagnetic field comprises both an electric field and a magneticfield, and the reference to a sensor 126 for detecting theelectromagnetic field refers to a device for detecting anelectromagnetic field, an electric portion of the electromagnetic field,and/or a magnetic portion of the electromagnetic field. A magnetic fielddetector may refer to a device for detecting a magnetic field. In anembodiment, a magnetic field detector may also be present at eachlocation at which an electromagnetic field detector is placed, thoughits presence may not be specifically mentioned throughout the remainderof the description for the purpose of clarity. The magnetic field may bedetected and processed using similar processing to that described hereinfor the detected electromagnetic field.

The sensor 126 may be used to detect a signal of interest 124 within theearth 108 while being disposed above the surface of the earth 108. Thesignal of interest may include the vertical component of theelectromagnetic field and/or the modulated, vertical component of theelectric field 124 in the near surface of the earth 108 resultingultimately from the coupling of an electromagnetic field 106 with aformation containing a fluid of interest. In an embodiment, the signalof interest may comprise and/or be indicative of a time-varyingelectromagnetic field within and/or above the surface of the earth 108.The electromagnetic signal 106 interacting with the formation maygenerally include the earth's background electromagnetic field, thoughother sources of electromagnetic radiation may result in interactionswith the formation of interest. In order to measure the signal ofinterest, the sensor 126 may measure the vertical portion of an electricfield in the near surface of the earth. As a result, the sensor 126 maycomprise any type of sensor capable of measuring the vertical electricfield 128 in the near surface of the earth. Additional signals may alsobe measured including the background vertical portion of the earth'selectromagnetic signal, the background cultural source electromagneticradiation, one or more components of the magnetic field, one or morehorizontal components of the electromagnetic signal and/or one or morecomponents of the seismic amplitude.

The sensor 126 may be placed at or on the surface of the earth 108 or atany distance above the surface of the earth (e.g., up to about onehundred feet) so long as the sensor 126 is within a detectable range ofthe vertical electric field in the earth. In an embodiment, the sensor126 may be placed up to about ten feet from the surface of the earth.The sensor 126 may be maintained in one location during the detection ofa signal and subsequently moved to provide another detection period.Alternatively, a plurality of sensors 126 may be used to provide aplurality of simultaneous measurements at multiple locations. Forexample, a plurality of sensors may be disposed in an array to allow fora plurality of measurements at multiple locations.

Still further, the sensor 126 may be moved during a measurement todetect the signal at multiple locations. Moving the sensor 126 mayresult in a degradation of the spatial resolution of the resultinganalysis, as described below, but may still provide information that canbe useful as a screening or first look at an area of interest. In anembodiment, the sensor 126 may be disposed in a moving vehicle. Suitablevehicles may include, but are not limited to, an airplane, anautomobile, and/or a boat in shallow water (e.g., a river). A recordingapparatus (e.g., element 304 of FIG. 4) may be used to record the signaldetected by the sensor 126, as described in more detail herein. In anembodiment, the sensor 126 may be used to continuously detect the signalof interest (e.g., while the sensor is moved), and the detected signalmay be recorded. Desired portions of the recorded signal may then beused in the systems and methods described below.

In an embodiment as shown in FIG. 4, the sensor 126 may comprise one ormore capacitive plates 301, 302 arranged parallel to the surface of theearth 108. The sensor 126 may be contained in suitable housing, and maycomprise a capacitor consisting of two parallel conductive plates 301,302. The conductive plates 301, 302 may be oriented generally parallelto the surface of the earth 108 to measure the vertical electric field.The conductive plates 301, 302 are preferably made from a conductivemetal such as copper, aluminum, or stainless steel, and can be aboutseveral square inches in area to about several square feet in area. Thetime varying, vertical electric field may produce a charge on the areaof one of the conductive plates 301. The other plate of the conductiveplates 302 may be grounded to produce a capacitive charge for the sensor126. In an embodiment, a resistor may be coupled in series with thecharged conductive plate 301 and a recording apparatus 304 to dischargethe charged plate 301 and allow a time varying field to be measured. Theparallel plate design may detect only the vertical electric field due tothe capacitive nature of the sensor 126, which may not detect thehorizontal magnetic component of the electromagnetic signal. While twoplates 301, 302 are shown, the sensor 126 may include a single plate 301appropriately grounded through one or more resistive devices and coupledto a recording apparatus 304.

In an embodiment, the sensor 126 as shown in FIG. 3 may comprise one ormore antennas disposed on or above the surface of the earth. Suitableantennas may include, but are not limited to, a parallel-plate capacitorantenna comprising two or more parallel conducting plates, asingle-plate capacitor antenna comprising one electrode electricallycoupled to the earth, a monopole antenna comprising a conductingelement, a dipole antenna comprising two conducting elements, amulti-pole antenna comprising a plurality of conducting elements, adirectional antenna comprising conducting elements arranged to augment asignal amplitude in a particular direction, and a coil antennacomprising one or more coils of wire, and/or any combination thereof.

In an embodiment, the antenna may comprise a concentric electric dipole(CED). The CED comprises two electrodes in a concentric configuration.For example, the electrodes may comprise generally circular dipoles withan inner circular electrode disposed concentrically within an outercircular electrode. The electrodes may generally be aligned in a planethat is parallel with the plane of the surface of the earth. The CED maythen preferentially detect the vertical portion of the earth'selectromagnetic field that is substantially perpendicular to the planeof the CED, where the vertical portion of the earth's electromagneticfield may create a detectable potential difference between the twoelectrodes.

In an embodiment illustrated in FIG. 1, an electromagnetic fielddetector 104 may be disposed near or within the surface of the earth 108to measure the earth's naturally occurring electromagnetic field 106within the earth 108. The electromagnetic field detector 104 may be usedto detect the earth's naturally occurring electromagnetic field 106within the earth 108, or any component of the naturally occurringelectromagnetic field 106. The electromagnetic field detector 104 may beconfigured to measure the vertical component of the earth'selectromagnetic field within the earth. In an embodiment, one or moreelectromagnetic field detectors may be configured to measure ahorizontal component of the earth's electromagnetic field in one or twodimensions. For example, FIG. 5 illustrates additional electrode pairs406, 408 disposed in a horizontal alignment to measure one or morehorizontal components of the earth's electromagnetic field. In anembodiment, a single electromagnetic field detector may be configured tomeasure a plurality of components of the electromagnetic field (e.g., atwo-axis electromagnetic field detector, or a three-axis electromagneticfield detector).

Returning to FIG. 1, the electromagnetic field detector 104 disposedwithin the earth may be above or below the water table. In anembodiment, the electromagnetic field detector 104 may be disposed atany depth in the earth above the formation of interest. In anembodiment, the electromagnetic field detector 104 may be disposed atany depth in the earth within and/or below the formation of interest.Combinations of these depths may also be used, for example withelectromagnetic field detectors above, within, and/or below theformation of interest.

In an embodiment, the electromagnetic field detector 104 may comprise apair of electrodes 110, 112 in contact with the earth and disposedwithin the earth. For example, a first electrode 112 may be disposed ina hole drilled into the earth ranging from about 10 feet to about 15feet. A second electrode 110 may be disposed within about 1 foot toabout 3 feet of the surface of the earth, and the pair of electrodes110, 112 may be electrically coupled. In an embodiment, the pair ofelectrodes 110, 112 may be disposed within the earth at varying depthsas needed to form an electrical coupling with the earth.

In an embodiment, the electrodes may take the form of porous potelectrodes, which may use an appropriate salt and/or aqueous solution toform an electrical coupling with the earth. Suitable salts useful withthe electrodes 110, 112 may include, but are not limited to, coppersulfate, silver chloride, cadmium chloride, mercury chloride, leadchloride, and any combination thereof. In an embodiment, the electrodesmay include, but are not limited to, conductive electrodes such as rodsthat are driven into the ground and/or sheets of metal, mesh sheets,and/or wires buried in trenches or in shallow pits. The conductiveelectrodes may comprise a variety of conductive materials including, butnot limited to, copper, stainless steel, aluminum, gold, galvanizedmetal, iron, lead, brass, graphite, steel, alloys thereof, andcombinations thereof. In an embodiment, the electrodes may comprise aconductive electrode in contact with the earth and electrically coupledto a porous pot electrode.

In an embodiment as shown in FIG. 5, a plurality of suitableelectromagnetic field detectors 104 may be employed. The electromagneticfield detectors 104 may be disposed in a pattern or array. For example,an array of suitable electromagnetic field detectors may comprise fromabout 2 to about 1,000, or from about 10 to about 100 electromagneticfield detectors. In an embodiment as shown in FIG. 6, one or more of theelectromagnetic field detectors 104 may be disposed within a wellbore604. The wellbore 604 may be disposed below an array 606 of sensors 608(e.g., electromagnetic field detectors and/or seismic sensors asdescribed in more detail below) or outside an array 606 of sensors 608.In an embodiment, a plurality of electromagnetic field detectors 104 maybe used with one or more of the electromagnetic field detectors 104disposed in a wellbore 604, and one or more of the electromagnetic fielddetectors disposed above and/or within the earth outside the wellbore(e.g., using porous pot and/or conductive electrodes).

As shown in FIG. 5, suitable additional electric and/or magnetic fielddetectors 402 may be located near one or more detectors used for passivesurveying. In an embodiment, the electric and/or magnetic fielddetectors 402 may be located within about 10 yards, alternatively withinabout 100 yards, or alternatively within about 500 yards of one or moreof the detectors. In an embodiment, additional electromagnetic fielddetectors 412, 414, 416 configured to measure the electromagnetic fieldwithin the earth and/or electric and magnetic field detectors 418configured to measure the electromagnetic field above the surface of theearth may be located at a distance away from the seismic sensors 102 toidentify the electric and/or magnetic fields that occur over largedistances. In an embodiment, the additional detectors 412, 414, 416, 418may be located more than about 500 yards, alternatively more than aboutone half mile, alternatively more than about one mile, or alternativelymore than about 5 miles from the one or more detectors.

One or more recording devices may record the resulting electromagneticfield produced by the one or more sensors and/or detectors disposedabove and/or within the earth. A suitable recording device may includedigital and/or analog recording devices and/or non-transitory media thatmay, in an embodiment, be contained in a weather resistant enclosurecapable of recording data over days to weeks without human intervention.The recording apparatus may be contained in a recording vehicle, ahousing structure, or a weather resistant enclosure located proximatethe sensor. In an embodiment shown in FIG. 1, a suitable recordingdevice may be contained in a dedicated recording vehicle 130 for theelectromagnetic field detector 104. In an embodiment shown in FIG. 4,the recording device 304 may be coupled to the sensor 126, and therecording apparatus 304 may be internal or external to the sensor 126housing. In an embodiment shown in FIG. 6, the recording device 602 maybe one of a plurality of recording devices 130, 602 used to record oneor more electric and/or seismic signals.

The signals may be recorded over a length of time sufficient to allowfor analysis of the signals including a sufficient time to allow foraveraging and signal integration to ensure an adequate signal-to-noiseratio (SNR). In an embodiment, the signal may be recorded for at leastabout 2 times, at least about 3 times, at least about 4 times, at leastabout 5, times, at least about 10 times, at least about 20 times, atleast about 50 times, at least about 100 times, or at least about 1,000times the period of the signal of interest. In an embodiment, the signalmay be recorded at least about 0.1 seconds, at least about 5 seconds, atleast about 20 seconds, or at least about 30 seconds. Longer recordingtimes may allow for increasing reliability, but at the same time, theamount of data that must be processed is increased. In general, arecording time of from about 5 to about 6,000 seconds, about 200 toabout 1,200 seconds, or alternatively about 300 to about 900 secondswill be sufficient to analyze the data without generating excessive datato be processed. Longer recording times may be used, for example, whenthe sensor is moved during recording as when disposed in an airplane orautomobile. The signal may be converted into a digital signal using ananalog-to-digital converter with an appropriate sampling rate. Thesampling rate stored by the recording apparatus may vary, though someconsideration of the frequencies of interest may determine the minimumsampling rate.

The signals from the sensor/detector and/or the signals stored in therecording apparatus may be processed in real time. As used herein, “realtime” refers to a nearly contemporaneous processing of the detected datathough some processing delays may be present (e.g., due to latency inthe sensors and processing equipment). Thus, real time may refer to thehandling and/or processing of a signal within about five minutes of thegeneration of the corresponding signal. Alternatively, the storage ofthe signal in the recording apparatus may allow for subsequentprocessing and interpretation. As described above, the signal may beprocessed using an analog-to-digital converter to allow the signal to beprocessed by one or more digital signal processing components, such as adigital computer as described in more detail herein. For example, asignal processor 306 as illustrated in FIG. 4 may be used to process thesignal. In general, the sampling rate for the analog-to-digitalconversion should be at least twice the highest frequency of interest inorder to properly represent the recorded waveform. Higher sampling ratesare also possible and may include about 3 times, about 4 times, or about5 times the highest frequency of interest.

Passive Seismic Signal Detection Systems

As shown in FIG. 1, a seismic wave 120 may be detected by one or moreappropriate seismic sensors 102 positioned on and/or in the surface ofthe earth 108. In an embodiment, a plurality of seismic sensors 102 maybe used to detect the seismic wave 120 at multiple locations. As shownin FIG. 7, one or more seismic sensors 702 may be disposed within awellbore 704 (e.g., an existing wellbore, a new wellbore, a water well,a hydrocarbon well, etc.) for detecting a seismic wave within thesubsurface earth formation. The wellbore may extend through and/or belowthe formation of interest to allow for detection of the seismic wave atvarying depths in the earth. In an embodiment, the wellbore 704 may bedisposed below the array 706 of seismic sensors 102 and/or electricsensors/detectors or outside the array 706 of sensors. In an embodiment,one or more of the electromagnetic field detectors 104 shown in FIG. 6may be included in the same wellbore 704 as the one or more seismicsensors 702 as shown in FIG. 7 (e.g., the embodiments of FIG. 6 and FIG.7 may be combined). The seismic sensors 102, 702 may include, but arenot limited to, a geophone, a hydrophone, and/or an accelerometer (e.g.,a digital accelerometer). The geophone may comprise a single-componentgeophone, a two-component geophone, or a three-component geophone, andthe accelerometer may comprise a single-axis accelerometer, a two-axisaccelerometer, or a three-axis accelerometer. In an embodiment, theseismic sensor may comprise a three-component accelerometer.Combinations of these types of seismic sensors may be used when aplurality of seismic sensors are used to detect the seismic wave. Theseismic sensors 102, 702 may measure a seismic wave in multipledirections, for example in one or two directions parallel to the surfaceof the earth, in a direction perpendicular to the surface of the earth,and/or in a vertical direction.

Returning to FIG. 1, a detected seismic signal may be generated by eachseismic sensor 102. The detected seismic signal may represent or beindicative of the seismic wave 120 and may be suitably recorded, forexample, using a conventional seismic field recorder. In an embodiment,a suitable recording device may be contained in a recording vehicle 130,which may comprise a dedicated recording vehicle for the detectedseismic signal. Additional or alternative recording devices for thedetected seismic signal may also be used and may include digital and/oranalog recording devices and/or non-transitory media that may, in anembodiment, be contained in a weather resistant enclosure capable ofrecording data over days to weeks without human intervention. In anembodiment, each seismic sensor may have its own recording device, andeach recording device may be internal or external to the seismic sensor.The detected seismic signal may then be processed along with thedetected electromagnetic field to determine at least one property of thesubsurface earth formation. In an embodiment, the detected seismicsignal and the detected electromagnetic field may be processed inreal-time without first being recorded on a non-transitory medium.

When a plurality of seismic sensors is used to measure the seismic wave,the seismic sensors may be arranged in a variety of patterns. In anembodiment as shown in FIG. 5, a grid pattern may be used, and thespacing between the seismic sensors 102 may be less than about one halfof the wavelength of the highest frequency surface seismic wavesexpected to be encountered, which may include higher frequencies thanthose expected to be produced by the electroseismic effect within thesubsurface earth formation. Surface seismic waves may be due to varioussources including heavy equipment (e.g., construction equipment, trains,etc.), vehicular traffic, and/or natural sources (e.g., natural seismicactivity such as earthquakes, thunder, etc.).

In an embodiment as shown in FIG. 5, one or more seismic sensors 410 maybe used to measure one or more components of a seismic wave at adistance away from the seismic sensors 102 above the subsurface earthformation 420 of interest. In an embodiment, an additional seismicsensor 410 may be located at a distance away from the one or moreseismic sensors 102 to identify seismic waves from sources other thanthe subsurface earth formation and/or that occur over large distances.In an embodiment, the additional seismic sensors 410 may be located morethan about 500 yards, alternatively more than about one half mile,alternatively more than about one mile, or alternatively more than about5 miles from the one or more seismic sensors above the subsurface earthformation 420.

In an embodiment, the electromagnetic field detectors and seismicsensors disclosed herein may be used to perform passive surveying. Thesensors may be combined in any combination in order to obtain thedesired signals. For example, when a detected seismic signal is desired,a single seismic sensor or a plurality of seismic sensors may beemployed. Similarly, when a detected electromagnetic signal is desired,a single electromagnetic field detector or a plurality ofelectromagnetic field detectors may be employed. When both a detectedseismic signal and a detected electromagnetic signal are desired, asingle seismic sensor and a single electromagnetic field detector may beemployed, alternatively a single seismic sensor and a plurality ofelectromagnetic field detectors may be employed, alternatively, aplurality of seismic sensors and a single electromagnetic field detectormay be employed, or alternatively, a plurality of seismic sensors 120and a plurality of electromagnetic field detectors may be employed. Theelectromagnetic field detectors 104, 126 may be disposed in a pattern orarray, which in an embodiment may overlap with a pattern or array ofseismic sensors 102.

In an embodiment, any of the electromagnetic field detectors and/orseismic sensors disclosed herein may be used to perform long-termpassive surveying. In this embodiment, one or more of the signals may bedetected a plurality of times using the sensors. The signals may bedetected periodically (e.g., every week, every month, every year, etc.)or aperiodically over a period of hours, days, weeks, months, years,and/or decades. The long-term survey results may provide a time-basedindication of a subsurface earth formation of interest with respect totime, including any changes in the formation over the time period inwhich the signals are detected. Such a system may be used to monitor thedevelopment and/or depletion of a hydrocarbon field and/or water well oraquifer, for example during production of a fluid from the formation.

Passive Electrical Surveying and Processing: Detecting a ModulatingSignal

In an embodiment, passive surveying may be carried out by detecting anelectromagnetic signal alone, and processing the detectedelectromagnetic signal to determine if one or more fluids are present ina subterranean formation of interest. The electromagnetic signal maycomprise any of the electromagnetic signals described above including anonlinear electromagnetic response. In this embodiment, anelectromagnetic signal may be detected using any of the electromagneticfield detector configurations described above. In the broadest sense,the signal may be optionally pre-processed using one or more filters,followed by demodulation of the signal to determine if a modulation of acarrier signal (e.g., the earth's background electromagnetic field,electromagnetic radiation from a cultural source, a generated referencesignal, etc.) exists. The existence of a modulation of the carriersignal may be taken as a direct indication that a coupling has occurreddue to the interaction of the carrier signal with a modulating signalproduced in a subterranean formation below the sensor. Additionalprocessing may be performed including power spectral analysis andrelative power ratios of the modulating signal relative to a backgroundsignal to determine the frequency characteristics of the modulatingsignal. The frequency characteristics may be used to derive depth andlocation information about the source and strength of the modulatingsignal, thereby revealing information about the location of asubterranean formation. A variety of models may be used to correlate thespectral analysis results with the depth of the modulating signal.

Having generally described the various types of signal analysis that canbe performed on the detected electromagnetic signal, each signalprocessing method will now be described in greater detail. As discussedabove, the source signal interacting with the formation of interest maycomprise a broad spectrum of frequencies, from sub-hertz frequencies totens of thousands of hertz frequencies. While not intended to be limitedby theory, the modulating signal arising from the interactions withinthe formation of interest may have a narrower frequency-band spectrumthan the source signal with recognizable and extractablecharacteristics. Even with the narrower frequency-band characteristics,some pre-processing of the signal may be used to analyze the detectedsignal. The optional pre-processing of the signal may include use ofnoise reduction, separation of a direct current component of the signal,data reduction, and/or noise filtering/frequency band-passing.

A noise reduction scheme may be used to generate a signal that may havean increased signal-to-noise ratio relative to the full spectrum of theelectromagnetic field in the earth. In an embodiment as shown in FIG. 8,a reference signal 806 may be generated by a reference signal generator802 and introduced into the near surface of the earth, for example, bytransmitting the reference signal into the earth from a location near tothe ground 108. The modulating signal 124 may act to modulate thereference signal 806 in the same way as the vertical portion of theelectric field within the earth. Upon detecting the modulated referencesignal 808 with the sensor 104, various detection methods may then beused to compare the detected signal 808 with the known reference signal806 and isolate the modulating signal 124 for further processing. Thedetected, modulated reference signal 808 may, in some embodiments, befiltered or otherwise pre-processed prior to being compared andisolating the modulating signal 124. In an embodiment, a lock-inamplifier 804 may be used to isolate the modulating signal 124 from thedetected signal 808. The lock-in amplifier 804 may be of any type knownin the art and may receive as inputs the reference signal 802 and thedetected signal 808 from the sensor 104. For example, the referencesignal generator 802 may be coupled to the lock-in amplifier 804 or mayform a part of the lock-in amplifier 804. The lock-in amplifier 804 mayproduce a signal comprising the modulating signal 124 with a reducedsignal-to-noise ratio as compared to the signal detected by the sensor104. The produced signal may then be sent to one or more additional,optional pre-processing steps before being passed on for furtheranalysis.

Depending on the type of sensor used to detect the signal, the signalmay comprise both an alternating current (AC) portion and direct current(DC) portion. The DC portion of the signal may result from the detectionone or more portions of the earth's electromagnetic field and may notcontain data indicative of the modulating signal. The DC portion maythen be thought of as noise that may be filtered out prior to analysisof the signal. Any suitable DC filtering methods and/or equipment may beused to remove the DC portion from the detected signal. When acapacitive plate sensor is used, the DC portion may be filtered outbased on the sensor design. Alternatively, a capacitive filter and/or adigital filter implemented in software on a computer may be used toremove the DC portion from the detected and/or stored signal.

As discussed above, the time period over which the signal is detectedand recorded and/or the sampling frequency of the signal may result in asignificant quantity of data to analyze. Greater amounts of datagenerally require more time to analyze and greater storage and computingcosts. As a result, the amount of data may be limited and/or reduced toallow for faster processing, especially when real time processing isdesired. While a reduced amount of data may lead to a less accurateanalysis, processing of a relatively small portion of the data mayprovide a faster, cheaper first look at the results of the survey.

The data may be limited in a number of ways. In an embodiment, thesignal data may be decimated. Decimating the data reduces the amount ofdata that is processed in the analysis steps and, therefore, reducesprocessing time and costs. Excessive decimation may reduce thereliability of the analysis to a certain extent, and thus the savings inprocessing times and costs must be weighed against reduced reliability.The signal data may typically be decimated down to an effective samplingrate approximating two times the highest frequency of interest whileallowing for an identification of the frequency characteristics in thedata. Higher decimation rates may be used, for example, when a faster,and possibly less accurate first look at the data is desired. Decimationof the data may be used alone or in addition to any of the otherpre-processing techniques described herein.

The signal data may be filtered to reduce the amount of noise andthereby increase the SNR of the signal and/or the signal may beband-pass filtered to isolate one or more frequency bands of interestfor use in the further analysis of the data. A noise filter may compriseany type of noise filter known in the art. For example, a high passfilter, a low pass filter, any suitable wide band frequency filter,and/or any suitable narrow band frequency filter may be used toeliminate noise. The earth's background electromagnetic field, acultural source of electromagnetic radiation, and/or the referencesignal, if used, may be used to determine the frequency range, amplituderange, and/or other parameters of a desired noise filter.

In some embodiments, a plurality of electromagnetic detectors may bedisposed in an array and may be used to detect one or more components ofthe electromagnetic signal. In an embodiment, a horizontal component ofthe detected electromagnetic signal may be used with a predictive filterto remove noise from the vertical component of the detectedelectromagnetic field. The predictive filter may utilize one horizontalcomponent or two horizontal components as detected by the one or moreelectromagnetic field detectors. This predictive filter may be appliedto each electromagnetic field detector of the plurality ofelectromagnetic field detectors.

In addition to, or in place of, the noise filter, a band-pass filter maybe used to isolate one or more frequency ranges of interest for purposeof extracting the envelope or demodulating the signal over thisfrequency range. A set of predetermined frequencies may be used as thebasis for filtering the detected signal for further processing. Thefrequency filters may improve the SNR of the signal. A variety ofband-pass filters may be used to produce one or more frequency filteredsignals useful for further processing. For example, band-pass filtersimplemented in hardware are known and may be suitable. Alternatively,band-pass filters may also be implemented in software, for example,using a digital processing environment on a computer encoded forprocessing of the data. Any of a number of known rational polynomialfunctions may be used alone or in combination with other functions toseparate the data for a particular frequency and/or frequency range fromthe data set as a whole, and in general those functions and processesmay be used as frequency filters. For example, linear phase filters,finite impulse response filters, forward infinite impulse responsefilters, reverse infinite impulse response filters, and the like may beused. When a plurality of band-pass filters are used to generate aplurality of signals, each band pass filter may have the same or mayhave different bandwidths. The correlation between the frequency of themodulating signal obtained from the envelope extracted from the signaland the depth of the formation of interest may be determined in a numberof ways, as described in more detail below.

In an embodiment, the detected signal amplitude may be averaged over oneor more frequencies and/or frequency ranges. In an embodiment, theaveraging of the detected electromagnetic field signal amplitude maycomprise averaging the signal amplitude at one or more fixedfrequencies. The frequencies may generally be selected from thosefrequencies present in the detected electric signal. In an embodiment,the one or more frequencies at which the detected signal can be averagedmay be selected from a range of frequencies between about 0.01 Hz andabout 10,000 Hz. The averaging process may comprise measuring the signalamplitude for a length of time that is longer (e.g., greater than atleast twice as long) than the period of oscillation of the signal at theselected frequency, and then averaging the signal amplitude over thedetection time period. The averaging may reduce the momentaryfluctuations in the detected electromagnetic field resulting from noisefluctuations that are not related to signals originating in the earth.Processing may further consist of averaging the signal amplitude at manyfrequencies over a range of frequencies. For example, the selectedfrequencies might be chosen to be separated by 1 Hz between 1 Hz and10,000 Hz.

When the signal has been pre-processed using any optional pre-processingsteps including band-passing the signal, the signal may pass to a signalenvelope extraction step to determine the envelope of the signal in theband of interest. The envelope of the signal may refer to the shape ofthe modulation of the signal. As discussed above, the modulation, andtherefore the envelope, can comprise one or more of a frequencymodulation, a phase modulation, or an amplitude modulation. An envelopedetector as known in the art may be used to extract the envelope of thesignal. The envelope detector may be implemented in hardware or softwareand may be used to demodulate the band-passed signal to extract thesignal envelope. The envelope detector may be used to extract the signalenvelope for a plurality of band-passed signals. Suitable demodulationtechniques and methods are known and may include the Hilbert transformmethod.

Once the signal envelope has been obtained, the envelope may be analyzedto determine the spectral properties. The spectral properties may allowfor comparison with one or more additional envelopes for additionalsignal bands from the originally detected signal. The spectralproperties may be determined in the frequency domain throughwell-established methods for calculating the Fourier Transform and thepower spectral density. For example, the power spectral density forvarious bands of frequencies may be calculated to give the power carriedby the envelope expressed in units of power per frequency. Alternativelyor in addition to the power spectral density, a Fourier Transform (e.g.,Fast Fourier Transform (FFT), complex FFT, etc.) may provide anindication of the frequency characteristics of the envelope (e.g., afrequency distribution). Further, the power spectral density and FFTcalculations may provide relative amplitudes of each of the frequenciesidentified. As used herein, the “spectral properties” may includeamplitude and frequency characteristics of a signal and/or envelopealong with other characteristics of the signal and/or envelope such asthe phase characteristics, etc. Calculation of the spectral propertiesmay be implemented in hardware and/or software. Calculation methods fordetermining the power spectral density and/or the FFT are known and maybe carried out using processing implemented on a digital computercomprising a processor, as described in more detail below. In anembodiment, one or more of the spectral properties may be determinedusing a lock-in amplifier and/or a spectrum analyzer.

The spectral properties of one or more additional envelopes resultingfrom one or more corresponding additional frequency ranges selected fromthe detected (and optionally pre-processed) signal may be calculatedusing the methods described herein. When a plurality of spectralproperties has been calculated, the corresponding values may be comparedto generate one or more ratios of the spectral properties (e.g., powerspectral density, FFT amplitudes, phase comparisons, etc.) in certainfrequency bands to the corresponding spectral properties in otherfrequency bands. The spectral properties of the base detected signalcontaining various white noise portions may also be calculated using avariety of methods to provide a base spectral property (e.g., a powerdensity, a frequency-amplitude correlation, etc.) for comparison. Forexample, the base spectral property may be used to normalize the othercalculated ratios, though other mathematical transformations may be usedto produce similar results.

The ratios obtained by comparison of the various signal bands may beanalyzed and correlated as a function of the band-pass frequencies ofthe original signal and/or the frequency band of the extractedenvelopes. The resulting analysis may provide information about thefrequency characteristics of the modulating signal and/or an amplitudecorrelation relating the strength of the modulating signal for eachfrequency. Variations within the analysis may be used to adjust theanalysis criteria such as increasing the bandwidth of the band-passfilters, which may be expected to increase the amplitude of the ratio ofthe power spectral properties. The properties of the analysis may betailored based on the quality and amount of data obtained, the type ofsignals present and interacting with a formation of interest, and adesired processing speed and cost.

The existence of hydrocarbons in a formation may be indicated by theexistence of a modulating signal. In terms of the signal analysisdescribed in this section, the modulating signal may be identified bydemodulating a portion of the detected signal to determine if anenvelope can be identified. If no envelope is found that isdistinguishable from white noise, for example, or some other suitablereference signal, then this result may be taken as evidence that thereare no hydrocarbons in a formation of interest below the sensorlocation. If a suitable envelope is identified, then the analysisdescribed herein may be carried out to identify the spectral propertiesof the envelope and correlate the results with the presence of variousfluids as well as a frequency-depth function. In an embodiment, afurther survey as described below may be performed when an envelope isidentified.

Correlation of the spectral properties of the envelope and the presenceof various fluids in subterranean pore spaces may be based on a varietyof classification methodologies. For example, statistical regressionanalysis, and statistical classifiers such as neural networks, decisiontrees, Bayes-based classifiers, fuzzy logic-based classifiers, andconventional statistical classifiers may all be used to determine afrequency-depth relationship. For example, the analysis may be performedwith the system and methods described herein at locations with knownproperties and formation characteristics to train and/or determine thecorrelation parameters. Once the parameters have been determined (e.g.,once a neural net has been trained), the system and methods may berepeated in a new location.

While it is known that a correlation generally exists between thefrequency of the modulating signal and the depth at which it originates,the exact relationship may not be evident from the analysis of thesignal detected by the sensor. A frequency-depth function may beestablished using known locations, parameters, and/or calculations toallow the depth values for similar locations to be determined once thespectral characteristics of the signals are analyzed and determined. Thefrequency-depth relationship for electric signals may depend on theEarth's resistivity, formation properties, types of components present,and, more generally, the electrical properties for a particular area andcorrections may need to be applied to the spectral properties fromlocation to location. In some instances, the frequency-depth correlationvariation from area to area may not be so great that for many purposesan approximate or a more or less typical frequency-depth function may beused. For example, a frequency-depth function may be derived fromempirical data taking into consideration various locations that havebeen reported in the literature. This function may be considered more orless representative of the “typical” relationship between frequency anddepth. Other suitable sources of data may be considered including, forexample, an approximate frequency-depth function derived fromconventional skin effect conductivity analyses. The resulting typicalfrequency-depth function may be used to derive depth information for thecorresponding modulating signal of interest based on the analysisdescribed herein.

In still another embodiment, the various properties of the subterraneanformation including the frequency-depth function may be determined bydeveloping a geological model of the subterranean formation. Variousmodeling programs may be used to develop the model of the subterraneanformation and can provide predicted outputs based on the model. Thepredicted outputs can then be compared with the detected signals (e.g.,a detected envelope) to determine if the model is accurate. When adiscrepancy is detected, the geological model can be altered and theprocess repeated. Such a process may result in a match between thegeological model and the detected signal, thereby providing one or moreproperties of the subterranean formation.

The processing described herein may be used to determine the existenceof a fluid in a subterranean formation as well as other properties ofthe subterranean formation. In an embodiment, the processing of theelectromagnetic signal may provide an indication of at least oneproperty of a subterranean formation including, but not limited to, anexistence of the subsurface earth formation containing at least onefluid, a depth of the subsurface earth formation, a porosity, a fluidpermeability, a composition of at least one fluid within the subsurfaceearth formation, a spatial extent of the subsurface earth formation, anorientation of the boundaries of the subsurface earth formation, aresistivity, and any combination thereof. Further, the processing maydetect one or more fluids within the subterranean formation, wheredetectable fluids may include, but are not limited to, an aqueous fluid,a hydrocarbon, a petroleum, carbon dioxide and/or other reservoir gases(e.g., various acid gases, helium, and the like), and any combinationthereof.

While the measurement of a signal at a single location followed by ananalysis of that signal has been described herein, the detection andanalysis steps may be repeated any number of times. For example,multiple measurements may be made at a single location over several timeperiods. The results may be statistically analyzed to provide animproved accuracy correlation and/or survey. In addition, one or moresamples may be taken at varying locations sequentially in time orconcurrently in time using one or multiple sensors. For example,multiple measurements may be made at varying locations around a site ofinterest. Various grid patterns and/or random sample locations may bechosen to generate a plurality of measurements across an area. Forexample, the grid and/or array of detectors described above may be usedto generate a plurality of detected signals for use with the processingtechniques described herein. The multiple measurements may be performedsequentially or concurrently (e.g., using multiple sensors) at a singlelocation, and/or the measurements may be performed sequentially and/orconcurrently in the various locations around a site of interest when aplurality of locations are used to measure the signal of interest. Theresulting hydrocarbon indications and resulting depth measurements maybe used to generate a two dimensional, a three dimensional, and/or afour dimensional model (e.g., where the fourth dimension is time) of asubterranean formation and the one or more fluids contained therein.

Passive Electrical Surveying and Processing: Directly Detecting anElectromagnetic Field

In an embodiment, passive surveying may be carried out by detecting anelectromagnetic signal alone, and processing the detectedelectromagnetic signal to determine if one or more fluids are present ina subterranean formation of interest. The electromagnetic signal maycomprise the electromagnetic signals described above including anonlinear electromagnetic response. In this embodiment, anelectromagnetic signal may be detected using any of the electromagneticfield detector configurations described above. Once the electromagneticfield has been detected by one or more sensors and a signal has beengenerated, the signal may be analyzed to extract information concerningthe existence of a formation of interest. In the broadest sense, thesignal may be optionally pre-processed using one or more filters,followed by correlation analysis of the detected electromagnetic signalin either the time or frequency domain. The temporal or frequencycharacteristics of the correlation analysis may be used to derive depthand location information about the source and strength of the detectedsignal, thereby revealing information about the location of asubterranean formation. A variety of models may be used to correlate thecorrelation analysis results with the depth of the detected signal.

Having generally described the various types of signal analysis that canbe performed on the detected electromagnetic signal, each signalprocessing method will now be described in greater detail. As discussedabove, the source signal interacting with the formation of interest maycomprise a broad spectrum of frequencies, from sub-hertz frequencies totens of thousands of hertz frequencies. In an embodiment, the signal ofinterest may comprise the signal directly arising from theelectroseismic and seismoelectric effects within a formation ofinterest. While not intended to be limited by theory, theelectromagnetic signal arising from the interactions within theformation of interest may have a narrower frequency-band spectrum thanthe source signal with recognizable and extractable characteristics.Even with the narrower frequency-band characteristics, somepre-processing of the signal may be used to analyze the detected signal.The optional pre-processing of the signal may include use of a noisereduction detection scheme, separation of a direct current component ofthe signal, data reduction, and/or noise filtering/frequencyband-passing.

Depending on the type of sensor used to detect the signal, the signalmay comprise both an alternating current (AC) portion and direct current(DC) portion. The DC portion of the signal may result from the detectionof one or more portions of the earth's electromagnetic field and may notcontain signal of interest. The DC portion may then be thought of asnoise that may be filtered out prior to analysis of the signal. Anysuitable DC filtering methods and/or equipment may be used to remove theDC portion from the detected signal. When a capacitive plate sensor isused, the DC portion may be filtered out based on the sensor design.Alternatively, a capacitive filter and/or a digital filter implementedin software on a computer may be used to remove the DC portion from thedetected and/or stored signal.

As discussed above, the time period over which the signal is detectedand recorded and/or the sampling frequency of the signal may result in asignificant quantity of data to analyze. Greater amounts of datagenerally require more time to analyze and greater storage and computingcosts. As a result, the amount of data may be limited and/or reduced toallow for faster processing, especially when real time processing isdesired. While a reduced amount of data may lead to a less accurateanalysis, processing of a relatively small portion of the data mayprovide a faster, cheaper first look at the results of the survey.

The data may be limited in a number of ways. In an embodiment, thesignal data may be decimated. Decimating the data reduces the amount ofdata that is processed in the analysis steps and, therefore, reducesprocessing time and costs. Excessive decimation may reduce thereliability of the analysis to a certain extent, and thus the savings inprocessing times and costs must be weighed against reduced reliability.The signal data may typically be decimated down to an effective samplingrate approximating two times the highest frequency of interest whileallowing for an identification of the frequency characteristics in thedata. Higher decimation rates may be used, for example, when a faster,and possibly less accurate first look at the data is desired. Decimationof the data may be used alone or in addition to any of the otherpre-processing techniques described herein.

The signal data may be filtered to reduce the amount of noise andthereby increase the SNR of the signal and/or the signal may beband-pass filtered to isolate one or more frequency bands of interestfor use in the further analysis of the data. A noise filter may compriseany type of noise filter known in the art. For example, a high passfilter, a low pass filter, or any suitable wide band frequency filter,and/or any suitable narrow band frequency filter may be used toeliminate noise. The earth's background electromagnetic field, acultural source of electromagnetic radiation, and/or the referencesignal, if used, may be used to determine the frequency range, amplituderange, and/or other parameters of a desired noise filter.

In some embodiments, a plurality of electromagnetic sensors may bedisposed in an array and may be used to detect one or more components ofthe electromagnetic signal. In an embodiment, a horizontal component ofthe detected electromagnetic signal may be used with a predictive filterto remove noise from the vertical component of the detectedelectromagnetic field. The predictive filter may utilize one horizontalcomponent or two horizontal components as detected by the one or moreelectromagnetic field detectors. This predictive filter may be appliedto each electromagnetic field detector of the plurality ofelectromagnetic field detectors.

In addition to, or in place of, the noise filter, a band-pass filter maybe used to isolate one or more frequency ranges of interest for purposeof extracting the signal over this frequency range. A set ofpredetermined frequencies may be used as the basis for filtering thedetected signal for further processing. The frequency filters mayimprove the SNR of the signal. A variety of band-pass filters may beused to produce one or more frequency filtered signals useful forfurther processing. For example, band-pass filters implemented inhardware are known and may be suitable. Alternatively, band-pass filtersmay also be implemented in software, for example, using a digitalprocessing environment on a computer encoded for processing of the data.Any of a number of known rational polynomial functions may be used aloneor in combination with other functions to separate the data for aparticular frequency and/or frequency range from the data set as awhole, and in general those functions and processes may be used asfrequency filters. For example, linear phase filters, finite impulseresponse filters, forward infinite impulse response filters, reverseinfinite impulse response filters, and the like may be used. When aplurality of band-pass filters are used to generate a plurality ofsignals, each band pass filter may have the same or may have differentbandwidths.

In an embodiment, the detected signal amplitude may be averaged over oneor more frequencies and/or frequency ranges. In an embodiment, theaveraging of the detected electromagnetic field signal amplitude maycomprise averaging the signal amplitude at one or more fixedfrequencies. The frequencies may generally be selected from thosefrequencies present in the detected electric signal. In an embodiment,the one or more frequencies at which the detected signal can be averagedmay be selected from a range of frequencies between about 0.01 Hz andabout 10,000 Hz. The averaging process may comprise measuring the signalamplitude for a length of time that is longer (e.g., greater than atleast twice as long) than the period of oscillation of the signal at theselected frequency, and then averaging the signal amplitude over thedetection time period. The averaging may reduce the momentaryfluctuations in the detected electromagnetic field resulting from noisefluctuations that are not related to signals originating in the earth.Processing may further consist of averaging the signal amplitude at manyfrequencies over a range of frequencies. For example, the selectedfrequencies might be chosen to be separated by 1 Hz between 1 Hz and10,000 Hz.

When the signal has been pre-processed using any optional pre-processingsteps including band-passing the signal, the signal may be analyzed todetermine the spectral properties. The spectral properties may bedetermined in the frequency domain through well-established methods forcalculating the power spectral density. For example, the power spectraldensity for various bands of frequencies may be calculated to give thepower carried by the signal expressed in units of power per frequency.Further, the power spectral density calculations may provide relativeamplitudes of each of the frequencies identified. As used herein, the“spectral properties” may include amplitude and frequencycharacteristics of a signal. Calculation of the spectral properties maybe implemented in hardware and/or software. Calculation methods fordetermining the power spectral density are known and may be carried outusing processing implemented on a digital computer comprising aprocessor, as described in more detail below. In an embodiment, one ormore of the spectral properties may be determined using a lock-inamplifier and/or a spectrum analyzer.

Further processing of the obtained power spectral density may be done,including de-trending of the power spectral density and integration ofthe power spectral density. A correlation analysis of the detectedelectromagnetic field may then be performed in the time domain, thefrequency domain, or both. For example, a Fourier Transform or FastFourier Transform (FFT) of the power spectral density, perhaps afterprocessing steps such as de-trending and integration, can be performedto yield correlations between the source electromagnetic field andsecondary electromagnetic fields generated by seismic signals throughthe seismoelectric effect near the earth's surface, which in turn aregenerated by electroseismic effects at the formations of interest. Theproperties of the analysis may be tailored based on the quality andamount of data obtained, the type of signals present and interactingwith a formation of interest, and a desired processing speed and cost.

The existence of hydrocarbons in a formation may be indicated by theexistence of strong correlations between the source electromagneticsignal and the secondary electromagnetic field generated by seismicsignals through the seismoelectric effect near the earth's surface,which in turn are generated by electroseismic effects at the formationsof interest, at correlation times that correspond to known seismictransit times between hydrocarbon formations and the surface of theearth. These seismic transit times can be obtained explicitly fromseismic data obtained in the area of interest or can be estimated basedon rock acoustic properties.

The spectral properties may be correlated with the presence of variousfluids in subterranean pore spaces based on a variety of classificationmethodologies. For example, statistical regression analysis, andstatistical classifiers such as neural networks, decision trees,Bayes-based classifiers, fuzzy logic-based classifiers, and conventionalstatistical classifiers may all be used to determine a frequency-depthrelationship. For example, the analysis may be performed with the systemand methods described herein at locations with known properties andformation characteristics to train and/or determine the correlationparameters. Once the parameters have been determined (e.g., once aneural net has been trained), the system and methods may be repeated ina new location.

The correlations may also be used to develop a frequency-depth function.A frequency-depth function may be established using known locations,parameters, and/or calculations to allow the depth values for similarlocations to be determined once the spectral characteristics of thesignals are analyzed and determined. The frequency-depth relationshipfor electromagnetic signals may depend on the Earth's resistivity,formation properties, types of components present, and, more generally,the electrical properties for a particular area and corrections may needto be applied to the spectral properties from location to location. Insome instances, the frequency-depth correlation variation from area toarea may not be so great that for many purposes an approximate or a moreor less typical frequency-depth function may be used. For example, afrequency-depth function may be derived from empirical data taking intoconsideration various locations that have been reported in theliterature. This function may be considered more or less representativeof the “typical” relationship between frequency and depth. Othersuitable sources of data may be considered including, for example, anapproximate frequency-depth function derived from conventional skineffect conductivity analyses. The resulting typical frequency-depthfunction may be used to derive depth information for the correspondingdetected electromagnetic signal of interest based on the analysisdescribed herein. In an embodiment, the frequency-depth relationship isdetermined based on a classification method comprising at least onemethod selected from the group consisting of: a neural network, adecision tree, a Bayes-based classifier, a fuzzy logic-based classifier,and a conventional statistical classifier.

In still another embodiment, the various properties of the subterraneanformation including the frequency-depth function may be determined bydeveloping a geological model of the subterranean formation. Variousmodeling programs may be used to develop the model of the subterraneanformation and can provide predicted outputs based on the model. Thepredicted outputs can then be compared with the detected signals (e.g.,a detected electromagnetic signal) to determine if the model isaccurate. When a discrepancy is detected, the geological model can bealtered and the process repeated. Such a process may result in a matchbetween the geological model and the detected signal, thereby providingone or more properties of the subterranean formation.

The processing described herein may be used to determine the existenceof a fluid in a subterranean formation as well as other properties ofthe subterranean formation. In an embodiment, the processing of theelectromagnetic signal may provide an indication of at least oneproperty of a subterranean formation including, but not limited to, anexistence of the subsurface earth formation containing at least onefluid, a depth of the subsurface earth formation, a porosity, a fluidpermeability, a composition of at least one fluid within the subsurfaceearth formation, a spatial extent of the subsurface earth formation, anorientation of the boundaries of the subsurface earth formation, aresistivity, and any combination thereof. Further, the processing maydetect one or more fluids within the subterranean formation, wheredetectable fluids may include, but are not limited to, an aqueous fluid,a hydrocarbon, a petroleum, carbon dioxide, and any combination thereof.Other fluids know to be present in subsurface earth formations caninclude hydrogen sulfide, sulfur dioxide, helium, and the like.

While the measurement of a signal at a single location followed by ananalysis of that signal has been described herein, the detection andanalysis steps may be repeated any number of times. For example,multiple measurements may be made at a single location over several timeperiods. The results may be statistically analyzed to provide animproved accuracy correlation and/or survey. In addition, one or moresamples may be taken at varying locations sequentially in time orconcurrently in time using one or multiple sensors. For example,multiple measurements may be made at varying locations around a site ofinterest. Various grid patterns and/or random sample locations may bechosen to generate a plurality of measurements across an area. Forexample, the grid and/or array of detectors described above may be usedto generate a plurality of detected signals for use with the processingtechniques described herein. The multiple measurements may be performedsequentially or concurrently (e.g., using multiple sensors) at a singlelocation, and/or the measurements may be performed sequentially and/orconcurrently in the various locations around a site of interest when aplurality of locations are used to measure the signal of interest. Theresulting hydrocarbon indications and resulting depth measurements maybe used to generate a two dimensional, a three dimensional, and/or afour dimensional model (e.g., where the fourth dimension is time) of asubterranean formation and the one or more fluids contained therein.

Passive Seismic Surveying and Processing

In an embodiment, passive surveying may be carried out by detecting aseismic signal alone, and processing the detected seismic signal todetermine if one or more fluids are present in a subterranean formationof interest. In this embodiment, a seismic signal may be detected usingany of the seismic sensor configurations described above, including theuse of a plurality of seismic sensors configured in an array. Theseismic signal may comprise any of the seismic signals described aboveincluding a nonlinear seismic response.

Once the seismic signal has been detected by one or more seismic sensorsand a detected seismic signal has been generated, the signal may beanalyzed to extract information concerning the existence of a formationof interest. The analysis of the seismic signal may be similar to theanalysis of the detected electromagnetic signal described above. In thebroadest sense, the signal may be optionally pre-processed using one ormore filters, followed by analyzing the detected seismic signal todetermine if a seismic signal resulting from an electroseismicconversion is present. The existence of an a seismic signal resultingfrom an electroseismic conversion may be taken as a direct indicationthat a coupling has occurred due to the interaction of anelectromagnetic source with a fluid in a subterranean formation belowthe sensor. The frequency characteristics may be used to derive depthand location information about the source and strength of the detectedseismic signal, thereby revealing information about the location of asubterranean formation. A variety of models may be used to correlate thespectral analysis results with the depth of the modulating signal. Thecorrelation between the frequency of the filtered signal obtained fromthe raw seismic signal and the depth of the formation of interest may bedetermined in a number of ways, as described in more detail below.

Having generally described the various types of signal analysis that canbe performed on the detected seismic signal, each signal processingmethod will now be described in greater detail. As discussed above, thedetected seismic signal may be pre-processed using one or more filters.The optional pre-processing of the signal may include use of a noisereduction detection scheme, separation of a direct current component ofthe signal, data reduction, and/or noise filtering/frequencyband-passing.

As discussed above, the time period over which the seismic signal isdetected and recorded and/or the sampling frequency of the seismicsignal may result in a significant quantity of data to analyze. Greateramounts of data generally require more time to analyze and greaterstorage and computing costs. As a result, the amount of data may belimited and/or reduced to allow for faster processing, especially whenreal time processing is desired. While a reduced amount of data may leadto a less accurate analysis, processing of a relatively small portion ofthe data may provide a faster, cheaper first look at the results of thesurvey.

The data may be limited in a number of ways. In an embodiment, theseismic signal data may be decimated. Decimating the data reduces theamount of data that is processed in the analysis steps and, therefore,reduces processing time and costs. Excessive decimation may reduce thereliability of the analysis to a certain extent, and thus the savings inprocessing times and costs must be weighed against reduced reliability.The signal data may typically be decimated down to an effective samplingrate approximating two times the highest frequency of interest whileallowing for an identification of the frequency characteristics in thedata. Higher decimation rates may be used, for example, when a faster,and possibly less accurate first look at the data is desired. Decimationof the data may be used alone or in addition to any of the otherpre-processing techniques described herein.

The signal data may be filtered to reduce the amount of noise andthereby increase the SNR of the signal and/or the signal may beband-pass filtered to isolate one or more frequency bands of interestfor use in the further analysis of the data. A noise filter may compriseany type of noise filter known in the art. For example, a high passfilter, a low pass filter, or any suitable wide band frequency filter,and/or any suitable narrow band frequency filter may be used toeliminate noise. The earth's background electromagnetic field and/orlocal sources of seismic noise may be used to determine the frequencyrange, amplitude range, and/or other parameters of a desired noisefilter for the detected seismic signal.

In addition to, or in place of, the noise filter, a band-pass filter maybe used to isolate one or more frequency ranges of interest for purposeof filtering the detected seismic signal over a desired frequency range.A set of predetermined frequencies may be used as the basis forfiltering the detected signal for further processing. The frequencyfilters may improve the SNR of the signal. A variety of band-passfilters may be used to produce one or more frequency filtered signalsuseful for further processing. For example, band-pass filtersimplemented in hardware are known and may be suitable. Alternatively,band-pass filters may also be implemented in software, for example,using a digital processing environment on a computer encoded forprocessing of the data. Any of a number of known rational polynomialfunctions may be used alone or in combination with other functions toseparate the data for a particular frequency and/or frequency range fromthe data set as a whole, and in general those functions and processesmay be used as frequency filters. For example, linear phase filters,finite impulse response filters, forward infinite impulse responsefilters, reverse infinite impulse response filters, and the like may beused. When a plurality of band-pass filters are used to generate aplurality of signals, each band pass filter may have the same or mayhave different bandwidths.

In some embodiments, a plurality of sensors that may be disposed in anarray may be used to detect the seismic signal. In this embodiment,various optional pre-processing steps may use data from the plurality ofsensors to improve the signal-to-noise ratio and/or filter the resultingdetected signal. In an embodiment, local sources of noise may be presentin the vicinity of the seismic sensors, and the local sources of noisemay be rejected in the detected seismic signal using several methods.First, the detected seismic signals from one or more of the plurality ofseismic sensors may be filtered in the spatial domain to reject surfacewaves traveling across the plurality of seismic sensors. The filter mayuse at least a portion of the horizontal component of the detectedseismic signal across the plurality of seismic sensors to remove atleast a portion of a noise signal from the detected seismic signal ateach seismic sensor. In an embodiment, only a portion of the seismicsensors may be configured to measure a horizontal component of theseismic wave, and these seismic sensors may be used to generate thehorizontal components used in the spatial filter. In an embodiment, eachof the plurality of seismic sensors may be configured to measure ahorizontal component of the seismic wave, and each of the plurality ofseismic sensors may be used with the filter in the spatial domain toreject surface waves traveling across the plurality of seismic sensors.

In an embodiment, a horizontal component of the detected seismic signalmay be used as a predictive filter to remove local noise from thevertical component of each seismic sensor. The filter may utilize onehorizontal component or two horizontal components as detected by theseismic sensor. This predictive filter may be applied to each seismicsensor of the plurality of seismic sensors that is configured to measurea horizontal component of the seismic wave.

In an embodiment, local noise waves may propagate across the pluralityof seismic sensors in expected spreading patterns, which may beanalogous to water waves on a pond. The propagating noise waves may besuppressed by determining the direction of travel and speed, andapplying a spatial filter that makes use of the spreading symmetry ofthe noise wave. The spatial filter may remove the local noise from thedetected seismic signals at each sensor being affected by the noise. Inan embodiment, a predictive filter may be employed to predict thearrival and amplitude of the local noise wave at a seismic sensor andremove the local noise wave during the generation of the detectedseismic signal. In an embodiment, only a portion of the seismic sensorsmay be configured to measure a horizontal component of the seismic wave,and these seismic sensors may be used to determine the spreadinggeometry of the local noise wave. The spatial filter may then be appliedto each of the plurality of seismic sensors, including those that arenot configured to measure a horizontal component of the seismic wave. Inan embodiment, each of the plurality of seismic sensors may beconfigured to measure a horizontal component of the seismic wave, andeach of the plurality of seismic sensors may be used to predict andverify the spreading geometry of the local noise wave used with thespatial filter. In an embodiment, one or more additional seismic sensorsat a distance away from the plurality seismic sensors may be used tomeasure a seismic wave, which may include the local noise wave. Theability to measure the local noise wave at a distance from the pluralityof seismic sensors may provide better prediction of the local noise waveand an improvement of the reduction of the local noise wave in thedetected seismic signal.

In an embodiment, the detected seismic signals from the plurality ofseismic sensors may be cross-correlated, and the cross-correlated datafrom all of the seismic sensors may be summed. The resulting summed datamay be used as a predictive filter to enhance spatial continuity acrossthe plurality of seismic sensors. The summing of the data may result inan increase in the amplitude of the seismic waves arriving at the sametime, for example from a plane wave. Any seismic components resultingfrom a noise source traveling across the plurality of seismic sensorsand/or any components that are not traveling as a plane wave will tendnot to add. As a result, the summed data may be used to identify theseismic waves resulting from an electroseismic conversion and identifythe other seismic components as local noise sources.

In an embodiment, the assumption that the seismic wave resulting fromthe electroseismic conversion can be represented as a plane wave may beused to remove at least a portion of a noise signal from the detectedseismic signal from one or more of the seismic sensors. In anembodiment, a dip filter can be used to reject detected seismic signalsarriving at a non-normal angle to the plurality of seismic sensors. Inan embodiment, the dip filter may be applied after cross-correlating thedetected seismic signals from two or more of the seismic sensors.

In an embodiment, the detected seismic signal amplitude may be averagedover one or more frequencies and/or frequency ranges. In an embodiment,the averaging of the detected seismic signal amplitude may compriseaveraging the signal amplitude at one or more fixed frequencies. Thefrequencies may generally be selected from those frequencies present inthe detected seismic signal. In an embodiment, the one or morefrequencies at which the detected signal can be averaged may be selectedfrom a range of frequencies between about 0.01 Hz and about 1,000 Hz,alternatively between about 1 Hz and about 500 Hz. The averaging processmay comprise measuring the signal amplitude for a length of time that islonger (e.g., greater than at least twice as long) than the period ofoscillation of the signal at the selected frequency, and then averagingthe signal amplitude over the detection time period. The averaging mayreduce the momentary fluctuations in the detected seismic fieldresulting from noise fluctuations that are not related to signalsoriginating in the earth. Processing may further consist of averagingthe signal amplitude at many frequencies over a range of frequencies.For example, the selected frequencies might be chosen to be separated by1 Hz between 1 Hz and 500 Hz. Those skilled in the art of seismologywill recognize that the propagation of seismic waves from a subsurfacestructure to the earth's surface results in certain characteristic timesassociated with the time required for a seismic wave that originates ata subterranean formation to reach the Earth's surface where it isdetected. Processing passive seismoelectric data by the averagingprocess may include identifying the characteristic times of seismicpropagation from the subterranean formation. These characteristic timesmay then be processed by methods known to those skilled in the art todetermine the depth of subterranean structures.

When the seismic signal has been pre-processed using any optionalpre-processing steps including band-passing the signal, the seismicsignal may be analyzed to determine the spectral properties. Thespectral properties may be determined in the frequency domain throughwell-established methods for calculating the power spectral density. Forexample, the power spectral density for various bands of frequencies maybe calculated to give the power carried by the signal expressed in unitsof power per frequency. Further, the power spectral density calculationsmay provide relative amplitudes of each of the frequencies identified.As used herein, the “spectral properties” may include amplitude andfrequency characteristics of a seismic signal. Calculation of thespectral properties may be implemented in hardware and/or software.Calculation methods for determining the power spectral density are knownand may be carried out using processing implemented on a digitalcomputer comprising a processor, as described in more detail below. Inan embodiment, one or more of the spectral properties may be determinedusing a lock-in amplifier and/or a spectrum analyzer.

Further processing of the obtained power spectral density of the seismicsignal may be done, including de-trending of the power spectral densityand integration of the power spectral density. Finally, a FourierTransform or Fast Fourier Transform (FFT) of the power spectral density,perhaps after processing steps such as de-trending and integration, isperformed to yield correlations between the seismic signal generated byseismoelectric effects near the surface of the earth and the seismicsignals generated by electroseismic effects at the formations ofinterest. The properties of the analysis may be tailored based on thequality and amount of data obtained, the type of signals present andinteracting with a formation of interest, and a desired processing speedand cost.

The existence of hydrocarbons in a formation may be indicated by theexistence of strong correlations between the seismic signal generated byseismoelectric effects near the surface of the earth and the seismicsignals generated by electroseismic effects at the formations ofinterest, at correlation times that correspond to known seismic transittimes between hydrocarbon formations and the surface of the earth. Theseseismic transit times can be obtained explicitly from seismic dataobtained in the area of interest or can be estimated based on rockacoustic properties.

The spectral properties may be correlated with the presence of variousfluids in subterranean pore spaces based on a variety of classificationmethodologies. For example, statistical regression analysis, andstatistical classifiers such as neural networks, decision trees,Bayes-based classifiers, fuzzy logic-based classifiers, and conventionalstatistical classifiers may all be used to determine a frequency-depthrelationship. For example, the analysis may be performed with the systemand methods described herein at locations with known properties andformation characteristics to train and/or determine the correlationparameters. Once the parameters have been determined (e.g., once aneural net has been trained), the system and methods may be repeated ina new location.

The spectral properties may also be used to develop a frequency-depthfunction. A frequency-depth function may be established using knownlocations, parameters, and/or calculations to allow the depth values forsimilar locations to be determined once the spectral characteristics ofthe signals are analyzed and determined. The frequency-depthrelationship for seismic signals may depend on the Earth's resistivity,formation properties, types of components present, and, more generally,the electrical properties for a particular area and corrections may needto be applied to the spectral properties from location to location. Insome instances, the frequency-depth correlation variation from area toarea may not be so great that for many purposes an approximate or a moreor less typical frequency-depth function may be used. For example, afrequency-depth function may be derived from empirical data taking intoconsideration various locations that have been reported in theliterature. This function may be considered more or less representativeof the “typical” relationship between frequency and depth. Othersuitable sources of data may be considered including, for example, anapproximate frequency-depth function derived from conventional skineffect conductivity analyses. The resulting typical frequency-depthfunction may be used to derive depth information for the correspondingdetected electromagnetic signal of interest based on the analysisdescribed herein. In an embodiment, the frequency-depth relationship isdetermined based on a classification method comprising at least onemethod selected from the group consisting of: a neural network, adecision tree, a Bayes-based classifier, a fuzzy logic-based classifier,and a conventional statistical classifier.

In still another embodiment, the various properties of the subterraneanformation including the frequency-depth function may be determined bydeveloping a geological model of the subterranean formation. Variousmodeling programs may be used to develop the model of the subterraneanformation and can provide predicted outputs based on the model. Thepredicted outputs can then be compared with the detected signals (e.g.,a detected seismic signal) to determine if the model is accurate. When adiscrepancy is detected, the geological model can be altered and theprocess repeated. Such a process may result in a match between thegeological model and the detected signal, thereby providing one or moreproperties of the subterranean formation.

The processing described herein may be used to determine the existenceof a fluid in a subterranean formation as well as other properties ofthe subterranean formation. In an embodiment, the processing of theseismic signal may provide an indication of at least one property of asubterranean formation including, but not limited to, an existence ofthe subsurface earth formation containing at least one fluid, a depth ofthe subsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof. Further, the processing may detect one or morefluids within the subterranean formation, where detectable fluids mayinclude, but are not limited to, an aqueous fluid, a hydrocarbon, apetroleum, and any combination thereof.

While the measurement of a signal at a single location followed by ananalysis of that signal has been described herein, the detection andanalysis steps may be repeated any number of times. For example,multiple measurements may be made at a single location over several timeperiods. The results may be statistically analyzed to provide animproved accuracy correlation and/or survey. In addition, one or moresamples may be taken at varying locations sequentially in time orconcurrently in time using one or multiple sensors. For example,multiple measurements may be made at varying locations around a site ofinterest. Various grid patterns and/or random sample locations may bechosen to generate a plurality of measurements across an area. Forexample, the grid and/or array of detectors described above may be usedto generate a plurality of detected signals for use with the processingtechniques described herein. The multiple measurements may be performedsequentially or concurrently (e.g., using multiple sensors) at a singlelocation, and/or the measurements may be performed sequentially and/orconcurrently in the various locations around a site of interest when aplurality of locations are used to measure the signal of interest. Theresulting hydrocarbon indications and resulting depth measurements maybe used to generate a two dimensional, a three dimensional, and/or afour dimensional model (e.g., where the fourth dimension is time) of asubterranean formation and the one or more fluids contained therein.

Passive, Sequential Surveying and Processing

In an embodiment, passive surveying may be carried out by sequentiallydetecting and/or separately processing an electromagnetic signal and aseismic signal. For example, the detection of both an electromagneticsignal and a seismic signal may occur at different times and/orlocations. The two signals may be cross-correlated to some degree todetermine if one or more fluids are present in a subterranean formationof interest. In this embodiment, the seismic signal may be detectedusing any of the seismic sensor configurations described above,including the use of a plurality of seismic sensors configured in anarray. Similarly, the electromagnetic signal may be detected using anyof the electromagnetic sensor configurations described above, includingthe use of a plurality of electromagnetic sensors configured in anarray. The electromagnetic signal may comprise a modulatedelectromagnetic signal and/or the electromagnetic signal directlyoriginating from the electroseismic and seismoelectric conversions. Theelectromagnetic signal and/or the seismic signal may comprise nonlinearcomponents and/or responses.

The cross-correlation of the electromagnetic signal and the seismicsignal, which may also be referred to in some contexts as jointprocessing, may be used to identify the features that are common in bothdetected data sets. Electroseismic and seismoelectric signals originatein the same physical conversion mechanism at boundaries betweendissimilar rocks or at boundaries between different fluids in rock porespaces, as described in more detail above. However, the seismicdetectors and the electromagnetic field detectors may not be equallysensitive to rapid signal changes or to small signal amplitudedifferences. Thus, the processed electromagnetic signal and the seismicsignal may be similar but likely will not be identical. The use of across-correlation may be used to enhance and/or isolate the commoninformation in both data sets. Several methods are known to thoseskilled in the art for comparing the information in the two measurementswith the goal of learning more about subterranean features of interest.

In an embodiment, the cross-correlation of the electromagnetic signaland the seismic signal may be carried out at a variety of points in theanalysis of each signal as described above with respect to theprocessing of the electromagnetic signal alone and the seismic signalalone. In general, the cross-correlation of the electromagnetic signaland the seismic signal may be carried out on a data set using the sameor similar processing for each data set to allow for the comparison ofsimilar data sets. For example, both the electromagnetic signal and theseismic signal may be optionally pre-processed using one or more similarfilters and then cross-correlated. In other embodiments, theelectromagnetic signal and the seismic signal may be cross-correlatedfollowing the demodulation of the signal or after any additionalprocessing is performed.

The sequential detection and/or separate processing an electromagneticsignal and a seismic signal described herein may be used to determinethe existence of a fluid in a subterranean formation as well as otherproperties of the subterranean formation. In an embodiment, theprocessing of the electromagnetic signal and the seismic signal mayprovide an indication of at least one property of a subterraneanformation including, but not limited to, an existence of the subsurfaceearth formation containing at least one fluid, a depth of the subsurfaceearth formation, a porosity, a fluid permeability, a composition of atleast one fluid within the subsurface earth formation, a spatial extentof the subsurface earth formation, an orientation of the boundaries ofthe subsurface earth formation, a resistivity, and any combinationthereof. Further, the sequential detection and/or separate processingmay detect one or more fluids within the subterranean formation, wheredetectable fluids may include, but are not limited to, an aqueous fluid,a hydrocarbon, a petroleum, and any combination thereof

Passive, Simultaneous Surveying and Processing

In an embodiment, passive surveying may be carried out by detecting bothan electromagnetic signal and a seismic signal at overlapping timeintervals to allow for cross-correlation of the two detected signals.The resulting signals may then be processed to determine if one or morefluids are present in a subterranean formation of interest. In thisembodiment, an electromagnetic and seismic signal may be detected usingany of the sensor configurations described above, including the use of aplurality of sensors configured in an array.

In an embodiment, processing of the detected signals may comprisecross-correlating the detected electromagnetic field with the detectedseismic signal and isolating at least a portion of the detected seismicsignal arising from the electroseismic conversion. The ability toisolate the detected seismic signal arising from the electroseismicconversion may depend on the various components (e.g., desired signalversus noise components) of the detected electromagnetic field and/orthe detected seismic signal. For example, the amplitude of the earth'selectromagnetic field in the detected electromagnetic field and theseismic waves resulting from the electroseismic conversion within thesubsurface earth formation in the detected seismic signal may be smallerthan the various noise levels at the electromagnetic field detectorsand/or seismic sensors. Various processing techniques may be used whenan increase in the signal-to-noise ratio and/or removal of at least aportion of the noise in the detected electromagnetic field and thedetected seismic signals is needed. In an embodiment, at least oneprocessing technique may be used to eliminate at least a portion of acoherent noise and/or a random noise in the detected seismic signaland/or the detected electromagnetic field. Each of these processingtechniques will be described in more detail below.

Coherent noise refers to cyclic electromagnetic and/or seismic signalsthat have an approximately constant frequency over a predeterminedmeasurement period. Many coherent, electromagnetic noise sources can befound in a typical measurement setting and can be accounted for throughvarious processing techniques. For example, the power-line frequency of60 Hertz (Hz) can generate a high amplitude electromagnetic signal thatcan propagate into the earth, where the resulting amplitude at the oneor more electromagnetic field detectors may be hundreds or thousands oftimes larger than the desired background electromagnetic field withinthe earth. Similarly, unbalanced power-lines can generate 180 Hz noiseand motors can generate 400 Hz noise. As a further example, cathodicprotection circuits can produce poorly-rectified alternating current(AC) signals at several frequencies that result in electromagnetic noiseat the one or more electromagnetic field detectors. In order to improvethe signal-to-noise ratio, at least a portion of the noise may beremoved from the detected electromagnetic field.

In an embodiment, at least a portion of coherent noise may be removedfrom the detected electromagnetic field through the use of dataintervals having selected start times and durations. The intervals maybe non-overlapping and the start times may be chosen so that a portionof the detected electromagnetic field is not taken into consideration ina data interval. The data points within the data intervals may then besummed to remove at least a portion of the coherent noise and/or improvethe signal-to-noise ratio of the detected electromagnetic field throughcancellation of the overlapping coherent noise signal. In order tofacilitate the selection of the intervals, the detected electromagneticfield and the detected seismic signal may be recorded and the intervalsselected from the recorded data. In an embodiment, the intervals may beprocessed in real time, using for example a transitory storage medium,to temporarily store the data in the intervals during removal of thecoherent noise. In this embodiment, only the final signal having animproved signal-to-noise ratio and/or a reduced noise content may berecorded.

In an embodiment, a start time may be chosen to correspond to the zerocrossing voltage of a coherent noise source. For example, the start timefor a first interval may be selected to occur where the 60 Hz voltagecrosses zero volts. After collecting data for a given duration, thestart time for the next interval may be chosen as the zero crossingvoltage plus some additional time period. In an embodiment, theadditional time period may correspond to an irrational number or a wholenumber fraction of an irrational number. For example, the irrationalnumber may be π, though other irrational numbers may also be used. Forexample, the start time for the second interval in the example above maybe chosen to correspond to the 60 Hz zero crossing voltage plus a smalltime that is not an even fraction of the 60 Hz period, which is 16.666milliseconds (ms) for the 60 Hz signal. If the second and subsequentintervals have a predetermined start time corresponding to the 60 Hzzero crossing plus a cumulative time of π/10,000 (i.e., 0.31416microseconds (μs)) for each additional interval, then the collection ofthe data during the data interval will never repeat the 60 Hz phase ofthe first interval. In other words, each start time would begin 0.31416μs beyond the start time of the preceding interval relative to the timecorresponding to the zero crossing voltage. By adding a plurality of theresulting data intervals, the positive amplitudes (e.g., positivevoltage portions) of the coherent signals will cancel with the negativeamplitudes (e.g., negative voltage portions) of the coherent signalssuch that any coherent noise sources will not add up in the datacollection process. By this technique, at least a portion of thecoherent noise may be removed from the detected electromagnetic field.

In general, coherent noise sources may not have exactly constantfrequency over a predetermined measurement period. These imperfectionsmay be due to phase changes in the coherent noise sources. For example,electromagnetic noise generated by power lines can experience somevariations in the power-line voltage. The method described herein maycomprise monitoring the phase of the coherent noise source to adjust thestart times to correspond to the phase of the coherent noise for eachinterval. The coherent noise source may also experience amplitudevariations over time, which may result in a partial cancellation of thecoherent noise upon the summing of the intervals. In an embodiment, afrequency filter (e.g., a frequency notch filter) may be applied to thedetected electromagnetic field to further enhance the signal-to-noiseratio and/or reduce a portion of the coherent noise in the backgroundelectromagnetic field.

As a second coherent noise cancellation method, the start time may bechosen to correspond to events (e.g., large amplitude spikes) in the inthe earth's electric and/or magnetic fields. If these events occur atrandom intervals in time, then effective coherent noise cancellation maybe achieved through summing of the resulting data intervals. The numberof events may vary from location to location and from time to time. As aresult, this method may not yield as many data collection intervals perday as frequency based method, which may result in a slower datainterval collection.

Slower data collection resulting from choosing the predetermined starttime to correspond to an event in the earth's electric and/or magneticfields may be balanced by concentrating on the largest peak events inthe earth's electric and/or magnetic fields. Events comprising lowamplitude electric and/or magnetic fields may result in low-amplitudeseismic waves, which may be difficult to detect in the presence ofnoise. In order to select larger events and suppress the low amplitudepeaks in the earth's electric and/or magnetic fields, the detectedelectromagnetic field and the detected seismic signal data may besquared while retaining the sign. Cross-correlation of the squareddetected electromagnetic field and detected seismic signal data may thenresult in the selection of the largest events while suppressing thesmall-amplitude noise.

The duration of the data intervals may comprise any period of timesufficient to include at least one coherent noise cycle. The frequencyof the coherent noise, and thus the period of time of a coherent noisecycle, may be estimated based on localized sources of electromagneticnoise or measured using an electromagnetic field detector. In anembodiment, the predetermined duration comprises a time of at least aplurality of coherent noise cycles. In an embodiment, the durationcomprises a period of time of between about 10 seconds and about 100minutes, alternatively between about 30 seconds and about 10 minutes.

In an embodiment, each interval in the plurality of intervals does notoverlap with any other interval and each interval may have a period oftime between successive intervals in which the data are not considered.The period of time between intervals may be the same between eachinterval or may vary between the intervals. In an embodiment, the periodof time between the intervals may comprise an uneven fraction of acoherent noise cycle or an uneven fraction of a coherent noise cycleplus an amount of time corresponding to a whole number of coherent noisecycles. In an embodiment, the period of time between intervals maycomprise a fraction of π. For example, each interval may have a periodof time between intervals of a time of π/10,000 (i.e., 0.31416 μs), asdescribed in the example above. As an alternative example, one or morefull cycles of the coherent noise may be allowed to pass beforebeginning the next interval at a start time according to one of themethods disclosed herein. This may allow for system processing and/orrecording latencies to be taken into account between data intervals.

The techniques used to remove at least a portion of coherent noise fromthe detected electromagnetic field may also be applied to the detectedseismic signal. Various sources of coherent seismic noise may be presentin a typical measurement setting, including for example, motor noise,industrial equipment, etc. It should be noted that the start time andduration for each corresponding interval of both the detectedelectromagnetic field and the detected seismic signal are the same sothat the signals can be cross-correlated. In an embodiment, the starttime and duration may be chosen to allow cancellation of at least aportion of the coherent noise in both the detected electromagnetic fieldand the detected seismic signal.

In an embodiment, a method of removing at least a portion of a coherentnoise signal may use the techniques described above. In an embodiment, amethod comprises generating a detected electromagnetic field bydetecting the earth's electromagnetic field within the earth, andgenerating a detected seismic signal by detecting a seismic wave relatedto the earth's electromagnetic field. The detected electromagnetic fieldand the detected seismic signal may optionally be recorded, thoughprocessing of the detected signals without first being recorded may alsobe used. A first signal may be generated by adding a plurality ofintervals of the detected electromagnetic field, where each of theplurality of intervals of the detected electromagnetic field begins at astart time and continues for a duration. A second signal may begenerated by adding a plurality of intervals of the detected seismicsignal corresponding to the plurality of intervals of the detectedelectromagnetic field, wherein each of the plurality of intervals of thedetected seismic signal begins at the start time and continues for theduration. Processing of the first signal and the second signal may thenbe performed to determine at least one property of the subsurface earthformation. The number of the plurality of intervals may be chosen toproduce a predetermined signal-to-noise ratio and/or remove apredetermined amount of a coherent noise in one or more of the detectedsignals at one or more of the sensors.

Additional processing techniques may be used to eliminate at least aportion of a coherent noise and/or a random noise in the detectedelectromagnetic field and/or the detected seismic signal. As discussedabove, the electroseismic conversion between electromagnetic and seismicenergy may occur when ions in pore fluids are displaced relative tograin interfaces within the pores of a rock in a subsurface earthformation. The displaced ions may impose a force on the fluid in thepore space and the pore surfaces. The moving fluids and displaced ionsmay track each other and may be expected to have a corresponding, thoughnot necessarily identical, time dependence. In other words, theelectroseismic conversion may generate a seismic response to atime-dependent electromagnetic field with a corresponding timedependence. Accordingly, the resulting seismic wave may have the sametime-dependence as the earth's background electromagnetic field, onlydelayed by the seismic travel time. The electromagnetic signal traveltime may be neglected since the electromagnetic propagation time down tothe reservoir is much shorter than the seismic travel time to thesurface. This result may be used to remove at least a portion of a noisesignal that does not possess the expected time dependence between thedetected electromagnetic field and the detected seismic signal.

In addition to the expected time dependence, the seismic wavecharacteristics may be used to remove at least a portion of a noisesignal in the detected seismic signal. The detected seismic signalresulting from the electroseismic conversion of the earth's backgroundelectromagnetic field at a horizontal reservoir interface can be assumedto be a vertically-traveling plane wave, as described in more detailabove. Even inhomogeneous reservoir interfaces that on average arehorizontal can produce vertical plane waves. The vertical plane wave mayarrive at all of the seismic sensors at the same time, and accordingly,may not have any horizontal components. This result may be used toremove at least a portion of a noise signal by accounting for detectedseismic signal components that are not common to all of the seismicsensors and/or that do not represent a plane wave propagating from asubsurface earth formation.

In order to determine at least one property of the subsurface earthformation, the detected electromagnetic field and the detected seismicsignal may be processed, for example, using a cross-correlation of thedetected signals. Cross-correlation of the background electromagneticfield with the detected seismic signal from one or more seismic sensorsmay produce a peak in amplitude corresponding to the seismic traveltime. When a plurality of seismic sensors are used to generate one ormore detected seismic signals, the result of the cross-correlationbetween the background electromagnetic field and the detected seismicsignal should be the same for each seismic sensor. Local sources ofnoise (e.g., non-uniform noise sources) may corrupt this expectation,and the differences may be used to remove at least a portion of thenoise signal. For example, when considering a pseudo-random noise sourcewith a non-repeating character, the cross-correlation of the detectedelectromagnetic field and the detected seismic signal may be convolutedwith the autocorrelation of the detected electromagnetic field.

In an embodiment, local sources of noise may be rejected using severalmethods. First, the detected seismic signals from each of the seismicsensors may be filtered in the spatial domain to reject surface wavestraveling across the plurality of seismic sensors. The filter may use atleast a portion of the horizontal component of the detected seismicsignal across the plurality of seismic sensors to remove at least aportion of a noise signal from the detected seismic signal at eachseismic sensor. In an embodiment, only a portion of the seismic sensorsmay be configured to measure a horizontal component of the seismic wave,and these seismic sensors may be used to generate the horizontalcomponents used in the spatial filter. In an embodiment, each of theplurality of seismic sensors may be configured to measure a horizontalcomponent of the seismic wave, and each of the plurality of seismicsensors may be used with the filter in the spatial domain to rejectsurface waves traveling across the plurality of seismic sensors.

Second, a horizontal component of the detected seismic signal may beused as a predictive filter to remove local noise from the verticalcomponent of each seismic sensor. The filter may utilize one horizontalcomponent or two horizontal components as detected by the seismicsensor. This predictive filter may be applied to each seismic sensor ofthe plurality of seismic sensors that is configured to measure ahorizontal component of the seismic wave.

This noise cancellation method may also be used with the detectedelectromagnetic signal. In an embodiment, a horizontal component of thedetected electromagnetic signal may be used with a predictive filter toremove noise from the vertical component of the detected electromagneticfield. The predictive filter may utilize one horizontal component or twohorizontal components as detected by the one or more electromagneticfield detectors. This predictive filter may be applied to eachelectromagnetic field detector of the plurality of electromagnetic fielddetectors.

Third, local noise waves may propagate across the plurality of seismicsensors in expected spreading patterns, which may be analogous to waterwaves on a pond. The propagating noise waves may be suppressed bydetermining the direction of travel and speed, and applying a spatialfilter that makes use of the spreading symmetry of the noise wave. Thespatial filter may remove the local noise from the detected seismicsignals at each sensor having affected by the noise. In an embodiment, apredictive filter may be employed to predict the arrival and amplitudeof the local noise wave at a seismic sensor and remove the local noisewave during the generation of the detected seismic signal. In anembodiment, only a portion of the seismic sensors may be configured tomeasure a horizontal component of the seismic wave, and these seismicsensors may be used to determine the spreading geometry of the localnoise wave. The spatial filter may then be applied to each of theplurality of seismic sensors, including those that are not configured tomeasure a horizontal component of the seismic wave. In an embodiment,each of the plurality of seismic sensors may be configured to measure ahorizontal component of the seismic wave, and each of the plurality ofseismic sensors may be used to predict and verify the spreading geometryof the local noise wave used with the spatial filter. In an embodiment,one or more additional seismic sensors at a distance away from theplurality seismic sensors may be used to measure a seismic wave, whichmay include the local noise wave. The ability to measure the local noisewave at a distance from the plurality of seismic sensors may providebetter prediction of the local noise wave and an improvement of thereduction of the local noise wave in the detected seismic signal.

Fourth, the detected seismic signals may be cross-correlated, and thecross-correlated data from all of the seismic sensors may be summed. Theresulting summed data may be used as a predictive filter to enhancespatial continuity across the plurality of seismic sensors. The summingof the data may result in an increase in the amplitude of the seismicwaves arriving at the same time, for example from a plane wave. Anyseismic components resulting from a noise source traveling across theplurality of seismic sensors and/or any components that are nottraveling as a plane wave will tend not to add. As a result, the summeddata may be used to identify the seismic waves resulting from anelectroseismic conversion and identify the other seismic components aslocal noise sources.

Fifth, the assumption that the seismic wave resulting from theelectroseismic conversion can be represented as a plane wave may be usedto remove at least a portion of a noise signal from the detected seismicsignal from one or more of the seismic sensors. In an embodiment, a dipfilter can be used to reject detected seismic signals arriving at anon-normal angle to the plurality of seismic sensors. In an embodiment,the dip filter may be applied after cross-correlating the detectedseismic signals from two or more of the seismic sensors.

In an embodiment, the application of one or more of the methodsdisclosed here may result in the suppression of at least a portion of anoise source in a detected field and/or signal. When at least a portionof the noise source is removed, the cross-correlation between two ormore detected seismic signals may more closely approximate anautocorrelation of each detected seismic signal from each seismicsensor. Differences between the cross-correlation and theautocorrelation may be due, at least in part, to differences in thedetected seismic signal amplitudes at each seismic sensor due to groundinhomogeneities and/or seismic scattering. The processing of thedetected electromagnetic field and the detected seismic signal with areduction in at least one noise signal may then be used to determine atleast one property of the subsurface earth formation.

In addition to the detected electromagnetic field and the detectedseismic signal, other detected signals may also be used to determine atleast one property of the subsurface earth formation. For example,nonlinear electroseismic conversions may produce signals useful duringprocessing. In an embodiment, nonlinear, harmonic signals havingfrequency components at higher frequency harmonics of the source'sfundamental frequency (i.e., those frequencies present in the earth'sbackground electromagnetic field) may be detected as a result ofdistortions of the background electromagnetic field interacting with thesubsurface earth formation containing at least one fluid. The harmonicsignals may be processed alone or in conjunction with the fundamentalfrequencies of the detected seismic signal and/or the detectedelectromagnetic field to determine one or more properties of thesubsurface earth formation. In an embodiment, the harmonic signals maybe present, detected, and/or isolated in both the detectedelectromagnetic field and the detected seismic signal.

One or more harmonic signals may be detected and/or isolated in thedetected seismic signal using a variety of methods. In an embodiment,the detected seismic signal may be cross-correlated with the detectedelectromagnetic field. A frequency analysis of the data resulting fromthe cross-correlation may be used to identify frequencies in thedetected seismic signal that are higher than those present in thedetected electromagnetic field. The frequencies present in the detectedelectromagnetic field may then be used to remove (e.g., using a filter)at least a portion of the corresponding frequencies (e.g., thefundamental frequencies) from the detected seismic signal and detectand/or isolate one or more of the harmonic signals. In an embodiment,the harmonic signal may comprise a coherent harmonic signal.

In an embodiment, the harmonic signals may be detected and/or isolatedin the detected seismic signal by partially rectifying the detectedseismic signal and/or the harmonic signals detected and/or isolated fromthe detected seismic signal. The harmonic signals may resemble apartially-rectified sine wave, which may be asymmetrical about zeroamplitude. In an embodiment, the positive amplitudes may be larger thanthe negative amplitudes. The resulting asymmetry may be utilized byarbitrarily reducing the positive portions of the source waveform beforecross-correlation. In an embodiment, the negative amplitudes may belarger than the positive amplitudes. The resulting asymmetry may beutilized by arbitrarily reducing the negative portions of the sourcewaveform before cross-correlation. Signal measurement and processing maybe used to determine which portion of the amplitude (i.e., the positiveamplitude portion or the negative amplitude portion), if either, islarger.

The detected seismic signal may be filtered prior to cross-correlatingthe detected harmonic signals in the detected seismic signal with thedetected electromagnetic field and/or one or more harmonic signals inthe detected electromagnetic field, which are described in more detailbelow. An autocorrelation of the detected electromagnetic field may havelower frequency components than the autocorrelation of the detectedseismic signal from one or more of the seismic sensors. In anembodiment, the detected seismic signal may be band-pass filtered toremove frequencies below the fundamental frequencies present in thedetected electromagnetic field, which may be used to identify theharmonic signals. The filter may be applied before processing thedetected seismic signal and the detected electromagnetic field.

In an embodiment, the detected harmonic signals may be processed withthe detected electromagnetic field to determine at least one property ofthe subsurface earth formation. In an embodiment, the processing of thedetected harmonic signals with the detected electromagnetic field maycomprise cross-correlating the detected harmonic signals with thedetected electromagnetic field.

One or more nonlinear signals may be detected and/or isolated in thedetected electromagnetic signal using a variety of methods. Thenonlinear signals in the detected electromagnetic field, which mayinclude harmonic signals, may result from the conversion of theelectromagnetic energy in the earth's background electromagnetic fieldto seismic energy, as described in more detail above. This point ofconversion may also result in a frequency shift or time delay in theelectromagnetic energy in the earth's background electromagnetic field,generating nonlinear signals. At least a portion of the resultingnonlinear signals may be detected by the electromagnetic field detectorsand used to determine at least one property of the subsurface earthformation.

Without intending to be limited by theory, it is believed that the pointof electroseismic conversion may also produce nonlinear electromagneticconversions that may be detected and/or isolated in the detectedelectromagnetic signal. As discussed above, the electroseismic energyconversion may occur at the boundary between two types of rock. Forexample, the electroseismic energy conversion may occur at the boundarybetween reservoir rock and the sealing and/or confining rock.Alternatively, electroseismic energy conversion may occur at aninterface between pore fluids, for example, between oil and water. Atthe rock and/or fluid interfaces there may be a gradient in the chemicalpotential. For example, at the boundary between a silicate rock and acarbonate rock, a chemical reaction may occur in the comingled porefluids. For example, the silicate may dissolve the carbonate, and thesilicate ions in solution may react with the carbonate ions in solution.The overall reaction may be driven by a gradient in the chemicalpotential at the interface. The reaction product between positive andnegative ions in solution is electrically neutral and may precipitateout of solution. When a precipitate is formed, the resulting depositionof the precipitate strengthens the rock, increases it hardness, andincreases the electrical resistivity of the interface. During thereactions in pore spaces, concentration gradients of charged ions may becreated within the pore fluids.

These concentration gradients may produce an electrochemical-potentialgradient which may manifest itself as a macroscopic electrical potentialgradient. The internal electrical potential gradients at the interfacesmay create internal stresses, and the interaction of the earth'sbackground electromagnetic field with the electrochemical-potentialgradient may change these internal stresses. Due to the naturalmodulations in the earth's background electromagnetic field, theinternal stresses may be modulated, accounting for the nonlinearelectroseismic conversions that may be measured and used with thesystems and method disclosed herein.

In an embodiment, the interface where electroseismic conversions occurcan be modeled as a charged capacitor that comprises a planar region ofhigh resistance and an existing, internal electromagnetic field. Theinterface can then be understood as having a resistor-capacitor (RC)time constant. The RC time constant may vary over a considerable rangeof values depending on the resistance of the rock interface and theinternal electric field. The RC time constant may have the effect ofsmoothing out a portion of the background electromagnetic field, whichmay be detected by one or more of the electromagnetic field detectors.In an embodiment, the extent of the resulting smoothing of thebackground electromagnetic field may be used during processing todetermine at least one property of the subsurface earth formation.

The background electromagnetic field may be modified depending on theorientation of the background electromagnetic field with respect to theinterface. When the background electromagnetic field is parallel to theinternal electric field at the interface, the internal field andinternal stresses may not be modified significantly. In thisorientation, the interface behaves as a simple resistor of high valuewith mobile fluids in the pore space, and the RC time constant may notsignificantly affect the background electromagnetic field. However, someof the electrical field energy may be converted into seismic energy inthe electroseismic response.

When the background electromagnetic field is anti-parallel with respectto the internal field at the interface, the internal chemical reactionsmay be temporarily halted, the stresses and effective resistance may bereduced, and the net electric field may decrease. In this orientation,the applied field (e.g., the earth's background electromagnetic field)may be at least partially rectified to a reduced value and the change ininternal stresses may produce a seismic response. In terms of theoverall subsurface earth formation, the earth's backgroundelectromagnetic field may be at least partially rectified at theboundaries between rock masses. As a result, the earth's backgroundelectromagnetic field that is interacting with a charged dipole layerwhere an electroseismic conversion occurs may be altered, and thealterations may be detected by one or more background electromagneticfield detectors. By detecting and processing the resultingelectromagnetic field signals, at least one property of the subsurfaceearth formation may be determined.

In an embodiment, the partial rectification of the backgroundelectromagnetic field may be used to determine an orientation,resistivity, or both of at least one interface in the subsurface earthformation. The apparent subsurface resistivity may depend on thebackground electromagnetic field's polarization. In one polarity of thebackground electromagnetic field, the conversion surface looks like asimple resistor. In the opposite polarity it appears to be a capacitorwith a long RC time constant. This time constant may at least partiallysmooth out one polarity of the source signal, resulting in one polarityhaving an observable induced polarization while the opposite polaritymay not. The degree of induced polarization may act as an indicator ofthe resistivity of the interface, and the determination of the polaritybeing affected may act as an indicator of the orientation of the rockinterface.

The properties of the background electromagnetic field may be spatiallydependent, allowing for a determination of the lateral extent of thesubsurface earth formation structure. The extent of the lateralvariation in the induced polarization and generation of nonlinearsignals may be smoothed out due of the long wavelengths present in theearth's background electromagnetic field. As a result, the detectedelectromagnetic field may have a limited resolution with respect to theedges of the reservoir.

In an embodiment, low frequency measurements (e.g., below 1 Hz) of theearth's background electromagnetic field may be useful in measuring thepolarity dependence of the induced polarization. In the measurements ofthe seismic signals resulting from the electroseismic conversions, theseismic wavelengths may be useful for spatial delineation and theseismic velocity may be useful for depth determination. In thesemeasurements, frequency and time information may be importantcharacterizations. In an embodiment, the frequency and time informationmay be determined by integrating the amplitudes of different polaritiesin the detected electromagnetic field and the detected seismic signalfrom one or more seismic sensors.

The nonlinear signals in the detected electromagnetic field resultingfrom the conversions at the subsurface earth formation interfaces may bedetected using a variety of methods. In an embodiment, the positive andnegative polarities of the earth's background electromagnetic field mayhave different amplitudes and different frequency spectra after beingaffected by the interface. These differences may be used in determiningthe nonlinear components of the detected electromagnetic field. Theresulting linear electroseismic response may be detected from thedetected seismic signal at one or more seismic sensors. Through across-correlation, the resulting linear components of the detectedelectromagnetic field may be determined and isolated. Using the linearcomponents as a filter, the non-linear components may be isolated fromthe detected electromagnetic field. The filtered electromagnetic fieldmay be further processed to identify the nonlinear components or reduceany noise signals present in the remaining detected electromagneticfield after being filtered. For example, additional filters may beapplied and/or autocorrelations performed.

In an embodiment, the detected electromagnetic field may be compared tothe earth's background electromagnetic field measured at a distantlocation. The detected electromagnetic field may have harmonicfrequencies and low frequencies that are not present in a signalmeasured at a distant point. In this embodiment, a detectedelectromagnetic field at a distant electromagnetic field detector may beused to filter the detected electromagnetic field above the subsurfaceearth formation of interest. The remaining signal present after applyingthe filter may contain the various harmonic, nonlinear, and/or lowfrequencies of interest. These signals may be further processed orfiltered, for example to remove one or more noise signals.

In an embodiment, any harmonic, nonlinear, and/or low frequenciespresent in the detected electromagnetic field above the subsurface earthformation of interest may be detected by comparing the detectedelectromagnetic field measured in the earth to those measured in theatmosphere. If the earth's background electromagnetic field modulationcreates a seismic response, then the surface where energy conversionoccurs may behave as a source of electromagnetic radiation since thereis a finite region of modulated electromagnetic field and chargeseparation. The earth's background electromagnetic field within theearth may itself take on a character reflecting the nonlinearconversion. The resulting electromagnetic radiation may manifest itselfas a change in boundary conditions at the earth's surface. Specifically,the resulting electromagnetic radiation may create a vertical electricfield that may not be continuous across the earth/atmosphere boundary.The use of a detected electromagnetic field above the surface of theearth may be used to filter the detected electromagnetic field withinthe earth. The remaining signal present after applying the filter maycontain the various harmonic, nonlinear, and/or low frequencies ofinterest. These signals may be further processed or filtered, forexample to remove one or more noise signals.

The processing described herein may be used to determine the existenceof a fluid in a subterranean fluid as well as other properties of thesubterranean formation. In an embodiment, the processing of theelectric/electromagnetic signal and the seismic signal may provide anindication of at least one property of a subterranean formationincluding, but not limited to, an existence of the subsurface earthformation containing at least one fluid, a depth of the subsurface earthformation, a porosity, a fluid permeability, a composition of at leastone fluid within the subsurface earth formation, a spatial extent of thesubsurface earth formation, an orientation of the boundaries of thesubsurface earth formation, a resistivity, and any combination thereof.Further, the processing may detect one or more fluids within thesubterranean formation, where detectable fluids may include, but are notlimited to, an aqueous fluid, a hydrocarbon, a petroleum, and anycombination thereof.

As noted above, the detection and analysis steps described herein may berepeated any number of times. For example, multiple measurements may bemade at a single location over several time periods. The results may bestatistically analyzed to provide an improved accuracy correlationand/or survey. In addition, one or more samples may be taken at varyinglocations sequentially in time or concurrently in time using one ormultiple sensors. For example, multiple measurements may be made atvarying locations around a site of interest. Various grid patternsand/or random sample locations may be chosen to generate a plurality ofmeasurements across an area. For example, the grid and/or array ofdetectors (e.g., using about 10 to about 10,000 seismic sensors and/orelectromagnetic field detectors) described above may be used to generatea plurality of detected signals for use with the processing techniquesdescribed herein. The multiple measurements may be performedsequentially or concurrently (e.g., using multiple sensors) at a singlelocation, and/or the measurements may be performed sequentially and/orconcurrently in the various locations around a site of interest when aplurality of locations are used to measure the signal of interest. Theresulting hydrocarbon indications and resulting depth measurements maybe used to generate a two dimensional and/or three dimensional model ofa subterranean formation and the one or more fluids contained therein.

Additional Surveying Steps

In an embodiment, more information may be obtained about thesubterranean formation by conducting one or more further surveys afterany of the passive surveying techniques described herein have beencarried out. For example, a seismological survey, a controlled-sourceelectromagnetics survey, a controlled-source electroseismic survey, acontrolled-source seismoelectric survey a gravity survey, and/or amagnetic survey may be conducted based on an indication of a fluid(e.g., a hydrocarbon) present in the subterranean formation of interest.In an embodiment, an additional passive survey may be performed asdescribed herein. The additional passive survey may provide for moredata over a greater number of sensors and/or detectors to obtain higherquality information about the subterranean formation. Thus, the systemand methods described herein may be used in combination with othersurveying techniques to provide information about a subterraneanformation of interest. In an embodiment, a wellbore may be commencedand/or drilled into the subterranean formation when an envelope isdetected in order to recover one or more hydrocarbons contained therein.

These systems and methods may have several advantages over previousprospecting techniques. The detection of an electroseismic conversionallows for the detection of an electromagnetic signal and a generatedseismic response, alone or in combination. As a result, the passivesurveying system allows for surveying without an active electromagneticenergy source, which may improve site safety and reduce anyenvironmental impacts. The reduction in the amount of equipment andpower, along with the corresponding reduced footprint at the measurementsite, represents an advantage over other surveying systems and methods.From an environmental and health perspective, the reduction intransportation, site preparation, and high energy sources may improvethe overall health and safety of the workers operating the equipment. Inaddition, the earth's naturally occurring electromagnetic fieldcomprises a broad spectrum of frequencies, from sub-hertz frequencies totens of thousands of hertz frequencies, along with a broad coverage overthe surface of the earth. This broad spectrum allows for a broad rangeof penetration depths from tens of meters to tens of kilometers.

Computer Based Implementations

The various methods disclosed herein for removing coherent and randomnoise sources and/or isolating and processing nonlinear signals may usereal-time processing or may use data that has been recorded (e.g., postprocessing). In an embodiment, one or more of the methods disclosedherein may be implemented on any computer with sufficient processingpower, memory resources, and network throughput capability to handle thenecessary workload placed upon it. FIG. 9 illustrates a typical,computer system suitable for implementing one or more embodimentsdisclosed herein. The computer system 980 includes a processor 982(which may be referred to as a central processor unit or CPU) that is incommunication with memory devices including secondary storage 984, readonly memory (ROM) 986, random access memory (RAM) 988, input/output(I/O) devices 990, and network connectivity devices 992. The processormay be implemented as one or more CPU chips.

It is understood that by programming and/or loading executableinstructions onto the computer system 980, at least one of the CPU 982,the RAM 988, and the ROM 986 are changed, transforming the computersystem 980 in part into a particular machine or apparatus having thenovel functionality taught by the present disclosure. It is fundamentalto the electrical engineering and software engineering arts thatfunctionality that can be implemented by loading executable softwareinto a computer can be converted to a hardware implementation by wellknown design rules. Decisions between implementing a concept in softwareversus hardware typically hinge on considerations of stability of thedesign and numbers of units to be produced rather than any issuesinvolved in translating from the software domain to the hardware domain.Generally, a design that is still subject to frequent change may bepreferred to be implemented in software, because re-spinning a hardwareimplementation is more expensive than re-spinning a software design.Generally, a design that is stable that will be produced in large volumemay be preferred to be implemented in hardware, for example in anapplication specific integrated circuit (ASIC), because for largeproduction runs the hardware implementation may be less expensive thanthe software implementation. Often a design may be developed and testedin a software form and later transformed, by well known design rules, toan equivalent hardware implementation in an application specificintegrated circuit that hardwires the instructions of the software. Inthe same manner as a machine controlled by a new ASIC is a particularmachine or apparatus, likewise a computer that has been programmedand/or loaded with executable instructions may be viewed as a particularmachine or apparatus.

The secondary storage 984 is typically comprised of one or more diskdrives or tape drives and is used for non-volatile storage of data andas an over-flow data storage device if RAM 988 is not large enough tohold all working data. Secondary storage 984 may be used to storeprograms which are loaded into RAM 988 when such programs are selectedfor execution. The ROM 986 is used to store instructions and perhapsdata which are read during program execution. ROM 986 is a non-volatilememory device which typically has a small memory capacity relative tothe larger memory capacity of secondary storage 984. The RAM 988 is usedto store volatile data and perhaps to store instructions. Access to bothROM 986 and RAM 988 is typically faster than to secondary storage 984.The secondary storage 984, the RAM 988, and/or the ROM 986 may bereferred to in some contexts as computer readable storage media and/ornon-transitory computer readable media.

I/O devices 990 may include printers, video monitors, liquid crystaldisplays (LCDs), touch screen displays, keyboards, keypads, switches,dials, mice, track balls, voice recognizers, card readers, paper tapereaders, or other well-known input devices.

The network connectivity devices 992 may take the form of modems, modembanks, Ethernet cards, universal serial bus (USB) interface cards,serial interfaces, token ring cards, fiber distributed data interface(FDDI) cards, wireless local area network (WLAN) cards, radiotransceiver cards such as code division multiple access (CDMA), globalsystem for mobile communications (GSM), long-term evolution (LTE),worldwide interoperability for microwave access (WiMAX), and/or otherair interface protocol radio transceiver cards, and other well-knownnetwork devices. These network connectivity devices 992 may enable theprocessor 982 to communicate with the Internet or one or more intranets.With such a network connection, it is contemplated that the processor982 might receive information from the network, or might outputinformation to the network in the course of performing theabove-described method steps. Such information, which is oftenrepresented as a sequence of instructions to be executed using processor982, may be received from and outputted to the network, for example, inthe form of a computer data signal embodied in a carrier wave.

Such information, which may include data or instructions to be executedusing processor 982 for example, may be received from and outputted tothe network, for example, in the form of a computer data baseband signalor signal embodied in a carrier wave. The baseband signal or signalembodied in the carrier wave generated by the network connectivitydevices 992 may propagate in or on the surface of electrical conductors,in coaxial cables, in waveguides, in an optical conduit, for example anoptical fiber, or in the air or free space. The information contained inthe baseband signal or signal embedded in the carrier wave may beordered according to different sequences, as may be desirable for eitherprocessing or generating the information or transmitting or receivingthe information. The baseband signal or signal embedded in the carrierwave, or other types of signals currently used or hereafter developed,may be generated according to several methods well known to one skilledin the art. The baseband signal and/or signal embedded in the carrierwave may be referred to in some contexts as a transitory signal.

The processor 982 executes instructions, codes, computer programs,scripts which it accesses from hard disk, floppy disk, optical disk(these various disk based systems may all be considered secondarystorage 984), ROM 986, RAM 988, or the network connectivity devices 992.While only one processor 982 is shown, multiple processors may bepresent. Thus, while instructions may be discussed as executed by aprocessor, the instructions may be executed simultaneously, serially, orotherwise executed by one or multiple processors. Instructions, codes,computer programs, scripts, and/or data that may be accessed from thesecondary storage 984, for example, hard drives, floppy disks, opticaldisks, and/or other device, the ROM 986, and/or the RAM 988 may bereferred to in some contexts as non-transitory instructions and/ornon-transitory information.

In an embodiment, the computer system 980 may comprise two or morecomputers in communication with each other that collaborate to perform atask. For example, but not by way of limitation, an application may bepartitioned in such a way as to permit concurrent and/or parallelprocessing of the instructions of the application. Alternatively, thedata processed by the application may be partitioned in such a way as topermit concurrent and/or parallel processing of different portions of adata set by the two or more computers. In an embodiment, virtualizationsoftware may be employed by the computer system 980 to provide thefunctionality of a number of servers that is not directly bound to thenumber of computers in the computer system 980. For example,virtualization software may provide twenty virtual servers on fourphysical computers. In an embodiment, the functionality disclosed abovemay be provided by executing the application and/or applications in acloud computing environment. Cloud computing may comprise providingcomputing services via a network connection using dynamically scalablecomputing resources. Cloud computing may be supported, at least in part,by virtualization software. A cloud computing environment may beestablished by an enterprise and/or may be hired on an as-needed basisfrom a third party provider. Some cloud computing environments maycomprise cloud computing resources owned and operated by the enterpriseas well as cloud computing resources hired and/or leased from a thirdparty provider.

In an embodiment, some or all of the functionality disclosed above maybe provided as a computer program product. The computer program productmay comprise one or more computer readable storage medium havingcomputer usable program code embodied therein to implement thefunctionality disclosed above. The computer program product may comprisedata structures, executable instructions, and other computer usableprogram code. The computer program product may be embodied in removablecomputer storage media and/or non-removable computer storage media. Theremovable computer readable storage medium may comprise, withoutlimitation, a paper tape, a magnetic tape, magnetic disk, an opticaldisk, a solid state memory chip, for example analog magnetic tape,compact disk read only memory (CD-ROM) disks, floppy disks, jump drives,digital cards, multimedia cards, and others. The computer programproduct may be suitable for loading, by the computer system 980, atleast portions of the contents of the computer program product to thesecondary storage 984, to the ROM 986, to the RAM 988, and/or to othernon-volatile memory and volatile memory of the computer system 980. Theprocessor 982 may process the executable instructions and/or datastructures in part by directly accessing the computer program product,for example by reading from a CD-ROM disk inserted into a disk driveperipheral of the computer system 980. Alternatively, the processor 982may process the executable instructions and/or data structures byremotely accessing the computer program product, for example bydownloading the executable instructions and/or data structures from aremote server through the network connectivity devices 992. The computerprogram product may comprise instructions that promote the loadingand/or copying of data, data structures, files, and/or executableinstructions to the secondary storage 984, to the ROM 986, to the RAM988, and/or to other non-volatile memory and volatile memory of thecomputer system 980.

In some contexts, a baseband signal and/or a signal embodied in acarrier wave may be referred to as a transitory signal. In somecontexts, the secondary storage 984, the ROM 986, and the RAM 988 may bereferred to as a non-transitory computer readable medium or a computerreadable storage media. A dynamic RAM embodiment of the RAM 988,likewise, may be referred to as a non-transitory computer readablemedium in that while the dynamic RAM receives electrical power and isoperated in accordance with its design, for example during a period oftime during which the computer 980 is turned on and operational, thedynamic RAM stores information that is written to it. Similarly, theprocessor 982 may comprise an internal RAM, an internal ROM, a cachememory, and/or other internal non-transitory storage blocks, sections,or components that may be referred to in some contexts as non-transitorycomputer readable media or computer readable storage media.

EXAMPLES

The disclosure having been generally described, the following examplesare given as particular embodiments of the disclosure and to demonstratethe practice and advantages thereof. It is understood that the examplesare given by way of illustration and are not intended to limit thespecification or the claims in any manner.

Example 1

Referring now to FIG. 10, the results of passive seismoelectricdetection used to detect and process electromagnetic waves are shown.The processing of the detected signal illustrates characteristic depthsof subterranean formations of interest. The data of FIG. 10 werecollected at Harris County Tex. The subterranean features of interestare aquifers that are well-characterized by standard measurement methodsand the depths of the subject aquifers are tabulated in the publicdomain. FIG. 10 displays the amplitude of seismoelectric signals on thevertical axis and the depth below the surface on the horizontal axis.The highest amplitude peaks on the data of FIG. 10 occur at depthscorresponding to the known aquifer depths, which are known to occur atabout 200 feet, about 300 feet, and about 400 feet. Additionally, thedata of FIG. 10 have a peak near 100 feet that is the expected signaloriginating from seismic waves traveling between the aquifers at 200 and300 feet.

Example 2

Referring now to FIG. 11, the results of passive electroseismic testingused to detect and process a seismic signal are shown. The processing ofthe seismic signal illustrates characteristic depths to subterraneanformations that were also detected with the seismoelectric testing ofExample 1. The seismic testing reveals additional subterraneanstructures not found with the seismoelectric test. Those skilled in theart will recognize that seismic waves have shorter wavelengths thanelectromagnetic waves. The shorter wavelengths of seismic waves enableseismic detectors to resolve additional structures that are not visibleto electromagnetic waves. FIG. 11 has peaks indicating structures near100 feet, 200 feet, 300 feet, and 400 feet. A peak at 24 feet isexpected as a seismic wave originating at the near-surface water table.Double peaks near 100 feet, 200 feet, and 400 feet are expected to arisefrom electroseismic conversions at both the top and bottom of aquifers.

Example 3

Referring now to FIG. 12, cross-correlation (i.e., joint processing) ofthe results of Example 1 (shown in FIG. 10) and Example 2 (shown in FIG.11) shows the features that are common in the FIG. 10 and FIG. 11 datasets. Electroseismic and seismoelectric signals originate in the samephysical conversion mechanism at boundaries between dissimilar rocks orat boundaries between different fluids in rock pore spaces. The seismicdetectors and the electromagnetic field detectors are not equallysensitive to rapid signal changes or to small signal amplitudedifferences. Thus, the processed data shown in FIGS. 10 and 11 aresimilar but not identical. FIG. 12 enhances the common information inboth data sets. There exist several methods known to those skilled inthe art for comparing the information in the two measurements with thegoal of learning more about subterranean features of interest.

Example 4

Referring now to FIG. 13, the results of passive detection used todetect and process electromagnetic fields are shown. The processing ofthe detected signal illustrates characteristic depths of subterraneanformations of interest. The data of FIG. 13 were collected in Texas. Thesubterranean features of interest are hydrocarbon reservoirs and strongseismic reflectors that have been previously characterized by standardseismic surveying techniques. FIG. 13 displays the amplitude ofseismoelectric signals on the vertical axis and the depth on thehorizontal axis. The highest amplitude peaks on the data of FIG. 13occur at time of about 0.2 seconds, 0.365 seconds, 0.608 seconds, and1.028 seconds. These seismic travel times correspond to strongreflectors measured in seismology and the strong reflector at 1.028seconds, corresponding to a depth of approximately 10,000 feet, is thedepth of a recently discovered reservoir. Other peaks in FIG. 13 alsocorrespond to known depths of strong seismic reflectors. The results ofFIG. 13 illustrate that the application of the techniques describedherein can be used to identify the depth of seismic reflectors andhydrocarbons in a subsurface formation.

System and Method Embodiments

Having described the systems and methods for passive surveying, variousembodiments will now be described.

1. In an embodiment, a method of passive surveying comprises: generatingone or more detected signals by passively detecting a signal generatedwithin a subsurface earth formation due to a seismoelectric response oran electroseismic response in at least one porous subsurface earthformation containing at least one fluid; and processing the one or moredetected signals to determine at least one property of the subsurfaceearth formation.

2. The method of embodiment 1, wherein generating the one or moredetected signals comprises: generating a detected electromagnetic fieldby detecting earth's electromagnetic field using an electromagneticfield detector; and wherein processing the one or more detected signalscomprises: demodulating a portion of the signal to identify an envelopeof the signal, wherein the envelope is indicative of the presence of thehydrocarbons; and analyzing the envelope to determine a value correlatedto a depth of the hydrocarbons in the subterranean formation.

3. The method of embodiment 2, wherein demodulating the portion of thesignal comprises extracting a frequency modulation, a phase modulation,an amplitude modulation, or any combination thereof from the signal.

4. The method of embodiment 3, wherein the envelope comprises at leastone of the frequency modulation, the phase modulation, or the amplitudemodulation.

5. The method of any of embodiments 2 to 4, wherein the sensor isdisposed on or above the surface of the earth.

6. The method of any of embodiments 2 to 5, wherein the sensor is movingduring the detection of the electromagnetic field.

7. The method of any of embodiments 2 to 6, wherein the sensor isdisposed in a moving vehicle.

8. The method of any of embodiments 2 to 7, further comprising recordingthe signal using a recording apparatus.

9. The method of embodiment 8, wherein the signal is recorded for atleast about 5 seconds.

10. The method of embodiment 8, wherein the signal is recorded for atleast about 0.1 seconds.

11. The method of any of embodiments 8 to 10, wherein the recordingapparatus comprises a digital or analog recording device.

12. The method of any of embodiments 2 to 11, wherein analyzing theenvelope comprises determining one or more spectral properties of theenvelope.

13. The method of any of embodiments 2 to 12, wherein the valuecomprises a frequency distribution of the envelope and the value iscorrelated to the depth of the hydrocarbons using a frequency-depthfunction.

14. The method of embodiment 13, wherein the frequency-depth function isderived using data from a known location.

15. The method of any of embodiments 2 to 14, further comprisingrepeating the detecting, demodulating, and analyzing a plurality oftimes.

16. The method of embodiment 15, wherein the repeating is performed at asingle location.

17. The method of embodiment 15, wherein the repeating is performed atdifferent locations.

18. The method of embodiment 17, wherein the repeating is performedsequentially or concurrently at each of the different locations.

19. The method of embodiment 17 or 18, wherein the different locationscorrespond to a plurality of grid positions.

20. The method of embodiment 19, further comprising generating amulti-dimension model of a subterranean formation using a plurality ofvalues, wherein at least one value of the plurality of values isdetermined at each corresponding grid position of the plurality of gridpositions.

21. The method of any of embodiments 2 to 20, further comprising:performing a further survey of the subterranean formation when anenvelope is identified.

22. The method of embodiment 21, wherein the performing of the furthersurvey comprises a seismological survey, a controlled-sourceelectromagnetics survey, a controlled-source electroseismic survey, agravity survey, a magnetic survey, or a passive survey.

23. The method of any of embodiments 2 to 22, wherein detecting theearth's electromagnetic field comprises measuring a vertical electriccomponent of the earth's electromagnetic field.

24. The method of embodiment 23, further comprising generating adetected magnetic field by detecting earth's magnetic field using amagnetic field detector, and processing the detected magnetic field withthe vertical electric component and the detected seismic signal.

25. The method of any of embodiments 2 to 24, wherein detecting theearth's electromagnetic field comprises measuring the earth'selectromagnetic field in at least one horizontal direction.

26. The method of any of embodiments 2 to 25, wherein the earth'selectromagnetic field comprises a time-varying electromagnetic field.

27. The method of any of embodiments 2 to 26, wherein the earth'selectromagnetic field is detected using a pair of porous pot electrodes.

28. The method of embodiment 27, wherein the pair of porous potelectrodes comprises at least one component selected from the groupconsisting of: copper sulfate, silver chloride, cadmium chloride,mercury chloride, and lead chloride.

29. The method of any of embodiments 2 to 28, wherein the earth'selectromagnetic field is detected using a plurality of pairs of porouspot electrodes.

30. The method of any of embodiments 2 to 29, wherein the earth'selectromagnetic field is detected using a pair of conductive electrodes.

31. The method of embodiment 30, wherein the pair of metal electrodescomprises at least one conductive material selected from the groupconsisting of: copper, stainless steel, aluminum, gold, galvanizedmetal, iron, lead, brass, graphite, and steel.

32. The method of any of embodiments 2 to 31, wherein the earth'selectromagnetic field is detected using a conductive electrode coupledto a porous pot electrode.

33. The method of any of embodiments 2 to 32, wherein the detectedelectromagnetic field is generated using one or more antennas disposedon or above a surface of the earth.

34. The method of embodiment 33, wherein the one or more antennascomprises at least one antenna selected from the group consisting of: aparallel-plate capacitor antenna comprising two or more parallelconducting plates, a single-plate capacitor antenna comprising oneelectrode electrically coupled to the earth, a monopole antennacomprising a conducting element, a dipole antenna comprising twoconducting elements, a multi-pole antenna comprising a plurality ofconducting elements, a directional antenna comprising conductingelements arranged to augment a signal amplitude in a particulardirection, a coil antenna comprising one or more coils of wire, and anycombination thereof.

35. The method of embodiment 33, wherein the one or more antennascomprise a concentric electric dipole.

36. The method of any of embodiments 2 to 35, wherein the at least oneproperty of the subsurface earth formation comprises at least oneproperty selected from the group consisting of: an existence of thesubsurface earth formation containing at least one fluid, a depth of thesubsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof.

37. The method of any of embodiments 2 to 36, wherein the at least onefluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

38. The method of embodiment 37 where the aqueous fluid comprises atleast one of potable water, fresh water, or brine.

39 The method of any of embodiments 2 to 38, wherein the detectedelectromagnetic field results, at least in part, from a natural eventcomprising at least one of: a electromagnetic fluctuation in theionosphere, and a naturally occurring electric discharge in theatmosphere.

40. The method of any of embodiments 2 to 39, further comprising aplurality of electromagnetic field detectors.

41. The method of embodiment 40, wherein the plurality ofelectromagnetic field detectors are arranged in an array.

42. The method of any of embodiments 2 to 41, wherein processing the oneor more detected signals further comprises: filtering the detectedelectromagnetic field.

43. The method of embodiment 42, wherein the filtering and processingoccur in real time.

44. The method of any of embodiments 42 to 43, wherein filteringcomprises filtering a direct current (DC) portion of the detectedelectromagnetic field prior to performing the processing.

45. The method of any of embodiments 42 to 44, wherein filteringcomprises decimating a data set representing the detectedelectromagnetic field prior to performing the processing.

46. The method of any of embodiments 42 to 45, wherein filteringcomprises using a noise filter.

47. The method of embodiment 46, wherein the noise filter comprises ahigh pass filter, a low pass filter, a wide band frequency filter, anarrow band frequency filter, or any combination thereof.

48. The method of any of embodiments 42 to 47, wherein filteringcomprises using one or more band-pass filters.

49. The method of embodiment 48, wherein at least one of the band-passfilters of the one or more band-pass filters comprises a linear phasefilter, a finite impulse response filter, a forward infinite impulseresponse filter, a reverse infinite impulse response filter, or anycombination thereof.

50. The method of any of embodiments 2 to 49, wherein generating the oneor more detected signals further comprises: generating at least onenonlinear electromagnetic field response by isolating the at least onenonlinear electromagnetic field response from the detectedelectromagnetic field; and wherein processing the one or more detectedsignals further comprises: processing the at least one nonlinearelectromagnetic field response to determine at least one property of thesubsurface earth formation.

51. In an embodiment, a method for identifying deposits in asubterranean formation comprises: obtaining a signal corresponding to avertical electric field in the earth from an area of interest, whereinthe signal comprises a modulating signal generated within thesubterranean formation; filtering the signal using a set ofpredetermined frequency bandwidths to generate a plurality of filteredsignals; identifying a plurality of envelopes, wherein each envelope ofthe plurality of envelopes corresponds to each filtered signal of theplurality of filtered signals; and analyzing the plurality of envelopesto determine one or more values correlated to a depth of the deposits inthe subterranean formation.

52. The method of embodiment 51, wherein the modulating signal isgenerated based on a combination of electroseismic and seismoelectriceffects due to interactions between the deposits in the subterraneanformation and interactions with a background electromagnetic field ofthe earth.

53. The method of embodiment 51 or 52, wherein the modulating signalcomprises at least one of a frequency modulation, a phase modulation, oran amplitude modulation.

54. The method of embodiment 53, wherein the envelope comprises at leastone of the frequency modulation, the phase modulation, or the amplitudemodulation.

55. The method of any of embodiments 51 to 54, further comprisingrecording the signal using a recording apparatus.

56. The method of any of embodiments 51 to 55, wherein the filtering,identifying, and analyzing occur in real time.

57. The method of any of embodiments 51 to 56, wherein a positiveidentification of a plurality of envelopes indicates the presence of afluid within a pore in the subterranean formation.

58. The method of any of embodiments 51 to 57, wherein a positiveidentification of a plurality of envelopes indicates the presence of afluid of a certain type within a pore in the subterranean formation.

59. The method of any of embodiments 51 to 58, further comprisingfiltering a direct current (DC) portion of the signal from the signalprior to identifying a plurality of envelopes.

60. The method of any of embodiments 51 to 59, further comprisingdecimating a data set representing the signal prior to identifying theplurality of envelopes.

61. The method of any of embodiments 51 to 60, further comprisingfiltering the signal with a noise filter.

62. The method of embodiment 61, wherein the noise filter comprises ahigh pass filter, a low pass filter, a wide band frequency filter, anarrow band frequency filter, or any combination thereof.

63. The method of any of embodiments 51 to 62, wherein a plurality ofband-pass filters is used to generate the plurality of filtered signals.

64. The method of embodiment 63, wherein at least one of the band-passfilters of the plurality of band-pass filters comprises a linear phasefilter, a finite impulse response filter, a forward infinite impulseresponse filter, a reverse infinite impulse response filter, or anycombination thereof.

65. The method of any of embodiments 51 to 64, wherein identifying aplurality of envelopes comprises using a Hilbert transform method.

66. The method of any of embodiments 51 to 65, wherein analyzing theplurality of envelopes comprises determining one or more spectralproperties of at least one of the plurality of envelopes.

67. The method of embodiment 66, wherein determining one or morespectral properties comprises calculating a power spectral density forthe at least one of the plurality of envelopes.

68. The method of embodiment 66 or 67, wherein determining one or morespectral properties comprises calculating a frequency profile using afast Fourier transform of the at least one of the plurality ofenvelopes.

69. The method of any of embodiments 66 to 68, wherein determining oneor more spectral properties comprises using at least one of a lock-inamplifier or a spectrum analyzer.

70. The method of any of embodiments 66 to 69, further comprisingcorrelating a ratio of at least one spectral property of at least onefrequency band from one or more envelopes of the plurality of envelopesto at least one corresponding spectral property of at least a secondfrequency band from the one or more envelopes of the plurality ofenvelopes.

71. The method of any of embodiments 51 to 70, further comprisingcorrelating the value to a depth of the deposits in the subterraneanformation.

72. The method of embodiment 71, wherein correlating comprisesdetermining a frequency-depth relationship.

73. The method of embodiment 72, wherein the frequency-depthrelationship is determined based on a classification method comprisingat least one method selected from the group consisting of: a neuralnetwork, a decision tree, a Bayes-based classifier, a fuzzy logic-basedclassifier, and a conventional statistical classifier.

74. The method of embodiment 72 or 73, wherein the frequency-depthrelationship is determined based on a regression analysis of a set ofknown empirical data.

75. The method of any of embodiments 66 to 74, further comprisinganalyzing the one or more spectral properties to determine arelationship between the one or more spectral properties and a presenceof a fluid in a pore in the subterranean formation based on aclassification method comprising at least one method selected from thegroup consisting of: a neural network, a decision tree, a Bayes-basedclassifier, a fuzzy logic-based classifier, and a conventionalstatistical classifier.

76. The method of any of embodiments 66 to 75, further comprisinganalyzing the one or more spectral properties to determine arelationship between the one or more spectral properties and a presenceof a fluid in a pore in the subterranean formation based on a regressionanalysis of a set of known empirical data.

77. The method of any of embodiments 51 to 76, further comprising:developing a geological model of the subterranean formation; obtainingone or more predicted envelopes from the geological model; comparing theone or more predicted envelopes to the plurality of envelopes; anddetermining one or more properties of the subterranean formation basedon the comparing.

78. The method of any of embodiments 51 to 77, further comprising:performing a further survey of the subterranean formation when anenvelope is identified.

79. In an embodiment, a method comprises: providing a sensor disposed onor above a surface of the earth; generating a reference signal;introducing the reference signal into the earth, wherein the referencesignal is modulated by a modulating signal generated within thesubterranean formation to generate a modulated reference signal;detecting the modulated reference signal; and processing the modulatedreference signal and the reference signal to isolate the modulatingsignal.

80. The method of embodiment 79 wherein the modulating signal comprisesat least one of a frequency modulation, a phase modulation, or anamplitude modulation.

81. The method of embodiment 79 or 80, wherein the modulating signal isgenerated based on at least one of an electroseismic effect or aseismoelectric effect due to an interaction between a fluid in asubterranean formation and a background electromagnetic field of theearth.

82. The method of any of embodiments 79 to 81, further comprisingrecording the modulated reference signal using a recording apparatus.

83. The method of embodiment 82, wherein the modulated reference signalis recorded for at least about 5 seconds.

84. The method of embodiment 82, wherein the modulated reference signalis recorded for at least about 0.1 seconds.

85. The method of any of embodiments 79 to 84, wherein processing themodulated reference signal comprises demodulating the modulatedreference signal.

86. The method of embodiment 85, wherein the demodulating comprisesusing a Hilbert transform method.

87. The method of any of embodiments 79 to 86, wherein processing themodulated reference signal and the reference signal comprises using alock-in amplifier receiving the modulated reference signal and thereference signal to isolate the modulating signal.

88. The method of any of embodiments 79 to 88, further comprising:performing a further survey of the subterranean formation when anenvelope is identified.

89. In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: one or more sensors coupled to aprocessor that detect one or more signals generated within a subsurfaceearth formation due to a seismoelectric response or an electroseismicresponse in at least one porous subsurface earth formation containing atleast one fluid; and an analysis tool, that when executed on theprocessor, configures the processor to: receive the one or more signalsfrom the one or more sensors; and process at least a portion of the oneor more signals to determine at least one property of the subsurfaceearth formation.

90. The system of embodiment 89, wherein the one or more sensorscomprise: one or more electromagnetic field detectors that measures theearth's electromagnetic field and produces a signal indicative of thedetected electromagnetic field; and wherein the analysis tool configuresthe processor to: receive the signal from the one or more sensors;demodulate a portion of the signal to identify an envelope of thesignal; analyze the envelope to determine one or more propertiesindicative of the presence of the hydrocarbons; and analyze the envelopeto determine the depth of the hydrocarbons in the subterraneanformation.

91. The system of embodiment 90, wherein the envelope of the signalcomprises at least one of a frequency modulation, a phase modulation, oran amplitude modulation.

92. The system of embodiment 90 or 91, further comprising a recordingapparatus coupled to the sensor and the analysis tool, wherein therecording apparatus is configured to record the signal.

93. The system of any of embodiments 90 to 92, wherein the analysis toolfurther configures the processor to: remove a direct current (DC)portion of the signal.

94. The system of any of embodiments 90 to 93, wherein the analysis toolfurther configures the processor to: decimate a data set representingthe signal.

95. The system of any of embodiments 90 to 94, wherein the analysis toolfurther configures the processor to: filter a noise component from thesignal.

96. The system of any of embodiments 90 to 95, wherein the analysis toolfurther configures the processor to: filter the signal using apredetermined frequency bandwidth.

97. The system of any of embodiments 90 to 96, wherein the analysis toolconfigures the processor to demodulate a portion of the signal using aHilbert transform.

98. The system of any of embodiments 90 to 97, wherein the analysis toolconfigures the processor to analyze the envelope to determine a spectralproperty of the envelope.

99. The system of embodiment 98, wherein the spectral property comprisesa power spectral density.

100. The system of embodiment 98, wherein the spectral propertycomprises a frequency distribution determined by a fast Fouriertransform.

101. The system of any of embodiments 90 to 100, wherein the analysistool further configures the processor to: correlate the envelope to adepth of the hydrocarbons in the subterranean formation.

102. The system of embodiment 101, wherein the analysis tool configuresthe processor to: correlate the envelope to a depth using afrequency-depth function.

103. The system of any of embodiments 90 to 102, wherein theelectromagnetic field detector comprises a plurality of pairs of porouspot electrodes, wherein each pair of porous pot electrodes areelectrically coupled.

104. The system of embodiment 103, wherein the pairs of porous potelectrodes comprise at least one component selected from the groupconsisting of: copper sulfate, silver chloride, cadmium chloride,mercury chloride, and lead chloride.

105. The system of any of embodiments 90 to 104, wherein theelectromagnetic field detector comprises a plurality of pairs ofconductive electrodes, wherein each pair of conductive electrodes areelectrically coupled.

106. The system of any of embodiments 90 to 105, wherein the pluralityof conductive electrodes comprises at least one conductive materialselected from the group consisting of: copper, stainless steel,aluminum, gold, galvanized metal, iron, lead, brass, graphite, steel,alloys thereof, and any combination thereof.

107. The system of any of embodiments 90 to 106, wherein theelectromagnetic field detector comprises a conductive electrode coupledto a porous pot electrode.

108. The system of any of embodiments 90 to 107, wherein the at leastone fluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

109. The system of embodiment 108, wherein the aqueous fluid comprisesat least one of potable water, fresh water, or brine.

110. The system of any of embodiments 90 to 109, wherein theelectromagnetic field detector comprises an antenna disposed on or abovethe surface of the earth.

111. The system of embodiment 110, wherein the antenna comprises atleast one antenna selected from the group consisting of: aparallel-plate capacitor antenna comprising two or more parallelconducting plates, a single-plate capacitor antenna comprising oneelectrode electrically coupled to the earth, a monopole antennacomprising a conducting element, a dipole antenna comprising twoconducting elements, a multi-pole antenna comprising a plurality ofconducting elements, a directional antenna comprising conductingelements arranged to augment a signal amplitude in a particulardirection, a coil antenna comprising one or more coils of wire, and anycombination thereof.

112. The system of embodiment 110, wherein the antenna comprises aconcentric electric dipole.

113. In an embodiment, a system for detecting a signal comprises: asignal generator configured to generate a reference signal and transmitthe reference signal into the earth, wherein the reference signal ismodulated by a modulating signal generated within a subterraneanformation and generates a modulated reference signal; a sensor disposedon or above a surface of the earth and coupled to a processor thatdetects the modulated reference signal; and a filter coupled to thesignal generator and the sensor, wherein the filter is configured toreceive the reference signal from the signal generator and the modulatedreference signal from the sensor, and process the modulated referencesignal and the reference signal to isolate the modulating signal.

114. The system of embodiment 113, wherein the sensor comprises one ormore capacitive plates arranged parallel to a surface of the earth.

115. The system of embodiment 113 or 114, wherein the filter comprises alock-in amplifier.

116. The system of any of embodiments 113 to 115, wherein the modulatingsignal comprises at least one of a frequency modulation, a phasemodulation, or an amplitude modulation.

117. In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: a memory comprising a non-transitorycomputer readable media; a processor; and an analysis tool, that whenexecuted on the processor, configures the processor to: receive one ormore signals from one or more sensors, wherein the one or more sensorsdetect one or more signals generated within a subsurface earth formationdue to a seismoelectric response or an electroseismic response in atleast one porous subsurface earth formation containing at least onefluid; and process at least a portion of the one or more signals todetermine at least one property of the subsurface earth formation.

118. The system of embodiment 117, wherein the one or more sensorscomprise one or more electromagnetic field detectors that measures theearth's electromagnetic field and produces a signal indicative of thedetected electromagnetic field; and wherein the analysis tool furtherconfigures the processor to: receive the signal from the one or moreelectromagnetic field detectors; demodulate a portion of the signal toidentify an envelope of the signal; analyze the envelope to determineone or more properties indicative of the presence of the hydrocarbons;and analyze the envelope to determine the depth of the hydrocarbons inthe subterranean formation.

119. A method of passive surveying comprising: generating one or moredetected signals by passively detecting a signal generated within asubsurface earth formation due to a seismoelectric response or anelectroseismic response in at least one porous subsurface earthformation containing at least one fluid; and processing the one or moredetected signals to determine at least one property of the subsurfaceearth formation.

120. The method of embodiment 119 wherein generating the one or moredetected signals comprises: generating a detected electromagnetic fieldby detecting earth's electromagnetic field using an electromagneticfield detector; and wherein processing the one or more detected signalscomprises: processing the detected electromagnetic field to determinethe at least one property of the subsurface earth formation.

121. The method of embodiment 120, wherein detecting the earth'selectromagnetic field comprises measuring a vertical electric componentof the earth's electromagnetic field.

122. The method of embodiment 121, further comprising generating adetected magnetic field by detecting earth's magnetic field using amagnetic field detector, and processing the detected magnetic field withthe vertical electric component.

123. The method of any of embodiments 120 to 122, wherein detecting theearth's electromagnetic field comprises measuring the earth'selectromagnetic field in at least one horizontal direction.

124. The method of any of embodiments 120 to 123, wherein the earth'selectromagnetic field comprises a time-varying electromagnetic field.

125. The method of any of embodiments 120 to 124, wherein the earth'selectromagnetic field is detected using a pair of porous pot electrodes.

126. The method of embodiment 125, wherein the pair of porous potelectrodes comprises at least one component selected from the groupconsisting of: copper sulfate, silver chloride, cadmium chloride,mercury chloride, and lead chloride.

127. The method of any of embodiments 120 to 126, wherein the earth'selectromagnetic field is detected using a plurality of pairs of porouspot electrodes.

128. The method of any of embodiments 120 to 127, wherein the earth'selectromagnetic field is detected using a pair of conductive electrodes.

129. The method of embodiment 128, wherein the pair of metal electrodescomprises at least one conductive material selected from the groupconsisting of: copper, stainless steel, aluminum, gold, galvanizedmetal, iron, lead, brass, graphite, and steel.

130. The method of any of embodiments 120 to 129, wherein the earth'selectromagnetic field is detected using a conductive electrode coupledto a porous pot electrode.

131. The method of any of embodiments 120 to 130, wherein theelectromagnetic field detector is disposed on or above the surface ofthe earth.

132. The method of any of embodiments 120 to 131, wherein theelectromagnetic field detector is moving during the generation of thedetected electromagnetic field.

133. The method of any of embodiments 120 to 132, wherein theelectromagnetic field detector is disposed in a moving vehicle.

134. The method of any of embodiments 120 to 133, wherein the detectedelectromagnetic field is generated using one or more antennas disposedon or above a surface of the earth.

135. The method of embodiment 134, wherein the one or more antennascomprises at least one antenna selected from the group consisting of: aparallel-plate capacitor antenna comprising two or more parallelconducting plates, a single-plate capacitor antenna comprising oneelectrode electrically coupled to the earth, a monopole antennacomprising a conducting element, a dipole antenna comprising twoconducting elements, a multi-pole antenna comprising a plurality ofconducting elements, a directional antenna comprising conductingelements arranged to augment a signal amplitude in a particulardirection, a coil antenna comprising one or more coils of wire, and anycombination thereof.

136. The method of embodiment 134, wherein the one or more antennascomprise a concentric electric dipole.

137. The method of any of embodiments 120 to 136, wherein the at leastone property of the subsurface earth formation comprises at least oneproperty selected from the group consisting of: an existence of thesubsurface earth formation containing at least one fluid, a depth of thesubsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof.

138. The method of any of embodiments 120 to 137, further comprisingrecording the detected electromagnetic field.

139. The method of embodiment 138, wherein the recording occurs for atleast about 5 seconds.

140. The method of embodiment 138, wherein the modulated referencesignal is recorded for at least about 0.1 seconds.

141. The method of any of embodiments 120 to 140, wherein the at leastone fluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

142. The method of embodiment 141 where the aqueous fluid comprises atleast one of potable water, fresh water, or brine.

143 The method of any of embodiments 120 to 142, wherein the detectedelectromagnetic field results, at least in part, from a natural eventcomprising at least one of: an electromagnetic fluctuation in theionosphere, and a naturally occurring electric discharge in theatmosphere.

144. The method of any of embodiments 120 to 143, further comprising aplurality of electromagnetic field detectors.

145. The method of embodiment 144, wherein the plurality ofelectromagnetic field detectors are arranged in an array.

146. The method of any of embodiments 120 to 145, further comprisingperforming a correlation analysis of the detected electromagnetic fieldin the time domain, the frequency domain, or both, wherein thecorrelation analysis provides an indication of a presence of the atleast one fluid.

147. The method of embodiment 146, wherein performing the correlationanalysis provides at least one of temporal characteristics or frequencycharacteristics.

148. The method of embodiment 147, further comprising deriving afrequency-depth function based on the temporal characteristics, thefrequency characteristics, or both.

149. The method of embodiment 148, wherein the frequency-depth functionis derived using data from a known location.

150. The method of any of embodiments 120 to 149, further comprisingrepeating the passively detecting, and processing a plurality of times.

151. The method of embodiment 150, wherein the repeating is performed ata single location.

152. The method of embodiment 150 or 151, wherein the repeating isperformed at different locations.

153. The method of any of embodiments 150 to 152, wherein the repeatingis performed sequentially or concurrently at each of the differentlocations.

154. The method of embodiment 153, wherein the different locationscorrespond to a plurality of grid positions.

155. The method of embodiment 154, further comprising generating amulti-dimension model of a subterranean formation using a plurality ofdetected electromagnetic field signals, wherein at least one signal ofthe plurality of signals is determined at each corresponding gridposition of the plurality of grid positions.

156. The method of any of embodiments 120 to 155, further comprising:performing a further survey of the subterranean formation when apresence of the at least one fluid is detected.

157. The method of embodiment 156, wherein the further survey comprisesa seismological survey, a controlled-source electromagnetics survey, acontrolled-source electroseismic survey, a controlled-sourceseismoelectric survey, a gravity survey, a magnetic survey, or a passivesurvey.

158. The method of any of embodiments 120 to 157, wherein processing theone or more detected signals further comprises: filtering the detectedelectromagnetic field.

159. The method of embodiment 158, wherein the filtering and processingoccur in real time.

160. The method of embodiment 158 or 159, wherein filtering comprisesfiltering a direct current (DC) portion of the detected electromagneticfield prior to performing the processing.

161. The method of any of embodiments 158 to 160, wherein filteringcomprises decimating a data set representing the detectedelectromagnetic field prior to performing the processing.

162. The method of any of embodiments 158 to 161, wherein filteringcomprises using a noise filter.

163. The method of embodiment 162, wherein the noise filter comprises ahigh pass filter, a low pass filter, a wide band frequency filter, anarrow band frequency filter, or any combination thereof.

164. The method of any of embodiments 158 to 163, wherein filteringcomprises using one or more band-pass filters.

165. The method of embodiment 164, wherein at least one of the band-passfilters of the one or more band-pass filters comprises a linear phasefilter, a finite impulse response filter, a forward infinite impulseresponse filter, a reverse infinite impulse response filter, or anycombination thereof.

166. The method of any of embodiments 120 to 165, wherein processing thedetected electromagnetic field comprises averaging an amplitude of thedetected electromagnetic field over one or more frequencies.

167. The method of embodiment 166, wherein the plurality of frequenciescomprises one or more fixed frequencies.

168. The method of embodiment 166 or 167, wherein the averagingcomprises measuring an amplitude of the detected electromagnetic fieldfor a length of time that is greater than a period of oscillation of thedetected electromagnetic field at the one or more frequencies; andaveraging the amplitude over the length of time.

169. The method of any of embodiments 120 to 168, wherein processing thedetected electromagnetic field comprises determining one or morespectral properties of the detected electromagnetic field.

170. The method of embodiment 169, wherein determining one or morespectral properties comprises using at least one of a lock-in amplifieror a spectrum analyzer.

171. The method of embodiment 169, wherein determining one or morespectral properties comprises determining a relative amplitude of eachfrequency at which an amplitude is determined.

172. The method of any of embodiments 169 to 171, further comprisinganalyzing the one or more spectral properties to determine arelationship between the one or more spectral properties and thepresence of the at least one fluid in the subterranean formation basedon a classification method comprising at least one method selected fromthe group consisting of: a neural network, a decision tree, aBayes-based classifier, a fuzzy logic-based classifier, and aconventional statistical classifier.

173. The method of any of embodiments 169 to 172, further comprisinganalyzing the one or more spectral properties to determine arelationship between the one or more spectral properties and a presenceof the at least one fluid in the subterranean formation based on aregression analysis of a set of known empirical data.

174. The method of any of embodiments 169 to 173, wherein determiningone or more spectral properties comprises calculating one or more powerspectral densities.

175. The method of embodiment 174, further comprising de-trending of theone or more power spectral densities.

176. The method of embodiment 174 or 175, further comprising integratingeach of the one or more power spectral densities.

177. The method of any of embodiments 174 to 176, further comprisingperforming a fast Fourier transform of the one or more power spectraldensities; and determining one or more correlations between a sourcesignal and the detected electromagnetic field based on the fast Fouriertransform.

178. The method of embodiment 177, wherein an existence of the one ormore correlations provides an indication of the presence of the at leastone fluid in the subterranean formation.

179. The method of embodiment 177 or 178, wherein the one or morecorrelations indicate one or more transit times between the subterraneanformation and the surface of the earth.

180. The method of embodiment 179, further comprising correlating theone or more transit times to a depth of the fluid in the subterraneanformation.

181. The method of embodiment 180, wherein the correlating is based onestimate rock acoustic properties of the earth.

182. The method of embodiment 180 or 181, wherein correlating comprisesdetermining a frequency-depth relationship.

183. The method of embodiment 182, wherein the frequency-depthrelationship is determined based on a classification method comprisingat least one method selected from the group consisting of: a neuralnetwork, a decision tree, a Bayes-based classifier, a fuzzy logic-basedclassifier, and a conventional statistical classifier.

184. The method of embodiment 182 or 183, wherein the frequency-depthrelationship is determined based on a regression analysis of a set ofknown empirical data.

185. The method of any of embodiments 120 to 184, further comprising:developing a geological model of the subsurface earth formation;determining at least one predicted result from the geological model;comparing the at least one predicted result to the detectedelectromagnetic field; and determining the at least one property of thesubsurface earth formation based on the comparing.

186. The method of any of embodiments 120 to 185, wherein generating theone or more detected signals further comprises: generating at least onenonlinear electromagnetic field response by isolating the at least onenonlinear electromagnetic field response from the detectedelectromagnetic field; and wherein processing the one or more detectedsignals further comprises: processing the at least one nonlinearelectromagnetic field response to determine at least one property of thesubsurface earth formation.

187. A system for identifying hydrocarbons in a subterranean formationcomprising: one or more sensors coupled to a processor that detect oneor more signals generated within a subsurface earth formation due to aseismoelectric response or an electroseismic response in at least oneporous subsurface earth formation containing at least one fluid; and ananalysis tool, that when executed on the processor, configures theprocessor to: receive the one or more signals from the one or moresensors; process at least a portion of the one or more signals todetermine at least one property of the subsurface earth formation.

188. The system of embodiment 187, wherein the one or more sensorscomprise: an electromagnetic field detector that measures the earth'selectromagnetic field and produces a signal indicative of the detectedelectromagnetic field; and wherein the analysis tool receives the signaland determines the at least one property of a subsurface earthformation.

189. The system of embodiment 188, wherein the electromagnetic fielddetector is disposed within the surface of the earth.

190. The system of embodiment 188 or 189, further comprising a pluralityof electromagnetic field detectors.

191. The system of any of embodiments 188 to 190, wherein the signalcomprises a vertical component of the earth's electromagnetic field.

192. The system of any of embodiments 188 to 191, wherein the signalcomprises at least one horizontal component of the earth'selectromagnetic field.

193. The system of any of embodiments 188 to 192, wherein the signal isindicative of a time-varying electromagnetic field.

194. The system of any of embodiments 188 to 193, wherein theelectromagnetic field detector comprises a plurality of pairs of porouspot electrodes, wherein each pair of porous pot electrodes areelectrically coupled.

195. The system of embodiment 194, wherein the pairs of porous potelectrodes comprise at least one component selected from the groupconsisting of: copper sulfate, silver chloride, cadmium chloride,mercury chloride, and lead chloride.

196. The system of any of embodiments 188 to 195, wherein theelectromagnetic field detector comprises a plurality of pairs ofconductive electrodes, wherein each pair of conductive electrodes areelectrically coupled.

197. The system of any of embodiments 188 to 196, wherein the pluralityof conductive electrodes comprises at least one conductive materialselected from the group consisting of: copper, stainless steel,aluminum, gold, galvanized metal, iron, lead, brass, graphite, steel,alloys thereof, and any combination thereof.

198. The system of any of embodiments 188 to 197, wherein theelectromagnetic field detector comprises a conductive electrode coupledto a porous pot electrode.

199. The system of any of embodiments 188 to 198, wherein the at leastone property of the subsurface earth formation comprises at least oneproperty selected from the group consisting of: an existence of thesubsurface earth formation containing at least one fluid, a depth of thesubsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof.

200. The system any of embodiments 188 to 199, further comprising arecording apparatus configured to record the signal on a non-transitorymedia.

201. The system of embodiment 200, wherein the recording apparatuscomprises a digital or analog recording device.

202. The system of any of embodiments 188 to 201, wherein the at leastone fluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

203. The system of embodiment 202, wherein the aqueous fluid comprisesat least one of potable water, fresh water, or brine.

204. The system of any of embodiments 188 to 203, wherein theelectromagnetic field detector comprises an antenna disposed on or abovethe surface of the earth.

205. The system of embodiment 204, wherein the antenna comprises atleast one antenna selected from the group consisting of: aparallel-plate capacitor antenna comprising two or more parallelconducting plates, a single-plate capacitor antenna comprising oneelectrode electrically coupled to the earth, a monopole antennacomprising a conducting element, a dipole antenna comprising twoconducting elements, a multi-pole antenna comprising a plurality ofconducting elements, a directional antenna comprising conductingelements arranged to augment a signal amplitude in a particulardirection, a coil antenna comprising one or more coils of wire, and anycombination thereof.

206. The system of embodiment 204, wherein the antenna comprises aconcentric electric dipole.

207. The system of any of embodiments 188 to 206, wherein the analysistool further configures the processor to: remove a direct current (DC)portion of the signal.

208. The system of any of embodiments 188 to 207, wherein the analysistool further configures the processor to: decimate a data setrepresenting the signal.

209. The system of any of embodiments 188 to 208, wherein the analysistool further configures the processor to: filter a noise component fromthe signal.

210. The system of any of embodiments 188 to 209, wherein the analysistool further configures the processor to: filter the signal using apredetermined frequency bandwidth.

211. In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: a memory comprising a non-transitorycomputer readable media; a processor; and an analysis tool, that whenexecuted on the processor, configures the processor to: receive one ormore signals from one or more sensors, wherein the one or more sensorsdetect one or more signals generated within a subsurface earth formationdue to a seismoelectric response or an electroseismic response in atleast one porous subsurface earth formation containing at least onefluid; and process at least a portion of the one or more signals todetermine at least one property of the subsurface earth formation.

212. The system of embodiment 211, wherein the one or more sensorscomprise an electromagnetic field detector that measures the earth'selectromagnetic field and produces a signal indicative of the detectedelectromagnetic field; and wherein the analysis tool configures theprocessor to receive the signal and determine the at least one propertyof a subsurface earth formation.

213. A method of passive surveying comprising: generating one or moredetected signals by passively detecting a signal generated within asubsurface earth formation due to a seismoelectric response or anelectroseismic response in at least one porous subsurface earthformation containing at least one fluid; and processing the one or moredetected signals to determine at least one property of the subsurfaceearth formation.

214. The method of embodiment 213, wherein generating the one or moredetected signals comprises: generating a detected seismic signal bypassively detecting a seismic wave generated within the subsurface earthformation due to the seismoelectric response or the electroseismicresponse in the at least one porous subsurface earth formationcontaining the at least one fluid using a seismic sensor, and whereinprocessing the one or more detected signals comprises processing thedetected seismic signal to determine the at least one property of thesubsurface earth formation.

215. The method of embodiment 214, wherein the seismic sensor comprisesat least one sensor selected from the group consisting of: a hydrophone,a single-component geophone, a two-component geophone, a three-componentgeophone, a single-axis accelerometer, a two-axis accelerometer, and athree-axis accelerometer.

216. The method of embodiment 214 or 215, wherein the at least oneproperty of the subsurface earth formation comprises at least oneproperty selected from the group consisting of: an existence of thesubsurface earth formation containing at least one fluid, a depth of thesubsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof.

217. The method of any of embodiments 214 to 216, further comprisingrecording the detected seismic signal.

218. The method of any of embodiments 214 to 217, wherein the at leastone fluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

219. The method of embodiment 218, wherein the aqueous fluid comprisesat least one of potable water, fresh water, or brine.

220. The method of any of embodiments 214 to 219, wherein the seismicsensor is disposed on the surface of the earth, within a wellbore, orboth.

221. The method of any of embodiments 214 to 220, further comprisingfiltering the detected seismic signal to generate a filtered signal.

222. The method of embodiment 221, wherein the filtering and processingoccur in real time.

223. The method of embodiment 221 or 222, wherein filtering comprisesdecimating a data set representing the detected seismic signal prior toperforming the processing.

224. The method of any of embodiments 221 to 223, wherein filtering thedetected seismic signal comprises using a noise filter.

225. The method of embodiment 224, wherein the noise filter comprises ahigh pass filter, a low pass filter, a wide band frequency filter, anarrow band frequency filter, or any combination thereof.

226. The method of any of embodiments 221 to 225, wherein filtering thedetected seismic signal comprises using a plurality of band-pass filtersto generate the filtered signal.

227. The method of embodiment 226, wherein at least one of the band-passfilters of the plurality of band-pass filters comprises a linear phasefilter, a finite impulse response filter, a forward infinite impulseresponse filter, a reverse infinite impulse response filter, or anycombination thereof.

228. The method of any of embodiments 214 to 227, further comprising:generating the detected seismic signal using a plurality of seismicsensors.

229. The method of embodiment 228, wherein processing the detectedseismic signal comprises: filtering at least a portion of a seismic wavetraveling in a direction perpendicular to vertical by applying a spatialfilter to the detected seismic signal from the plurality of seismicsensors.

230. The method of embodiment 229, wherein the spatial filter is based,at least in part, on the spreading symmetry of the seismic wavetraveling in the direction perpendicular to vertical.

231. The method of any of embodiments 228 to 230, wherein processing thedetected seismic signal comprises: removing a seismic noise from avertical component of the detected seismic signal by applying apredictive filter to the detected seismic signal based on using ahorizontal component of the detected seismic signal from the pluralityof seismic sensors.

232. The method of any of embodiments 228 to 231, wherein processing thedetected seismic signal comprises: applying a dip filter to the detectedseismic signal based on rejecting at least a portion of the detectedseismic signals from the plurality of seismic sensors that arrive at anon-normal angle to a surface, wherein the surface is defined by theplurality of seismic sensors.

233. The method of any of embodiments 214 to 232, wherein processing thedetected seismic signal comprises averaging an amplitude of the detectedseismic signal over one or more frequencies.

234. The method of embodiment 233, wherein the plurality of frequenciescomprises one or more fixed frequencies.

235. The method of embodiment 233 or 234, wherein the averagingcomprises measuring the detected seismic signal amplitude for a lengthof time that is greater than a period of oscillation of the signal atthe one or more frequencies; and averaging the detected seismic signalamplitude over the length of time.

236. The method of any of embodiments 214 to 235, wherein processing thedetected seismic signal comprises determining one or more spectralproperties of the detected seismic signal.

237. The method of embodiment 236, wherein determining one or morespectral properties comprises using at least one of a lock-in amplifieror a spectrum analyzer.

238. The method of embodiment 236 or 237, further comprising analyzingthe one or more spectral properties to determine a relationship betweenthe one or more spectral properties and the presence of the fluid in apore in the subterranean formation based on a classification methodcomprising at least one method selected from the group consisting of: aneural network, a decision tree, a Bayes-based classifier, a fuzzylogic-based classifier, and a conventional statistical classifier.

239. The method of any of embodiments 236 to 238, further comprisinganalyzing the one or more spectral properties to determine arelationship between the one or more spectral properties and a presenceof the fluid in a pore in the subterranean formation based on aregression analysis of a set of known empirical data.

240. The method of any of embodiments 236 to 239, wherein determiningone or more spectral properties comprises determining a relativeamplitude of each frequency at which an amplitude is determined.

241. The method of any of embodiments 236 to 240, wherein determiningone or more spectral properties comprises calculating a power spectraldensity.

242. The method of embodiment 241, further comprising de-trending of thepower spectral density.

243. The method of embodiment 241 or 242, further comprising integratingthe power spectral density.

244. The method of any of embodiments 241 to 243, further comprisingperforming a fast Fourier transform of the power spectral density; anddetermining one or more correlations between a source signal and thedetected seismic signal based on the fast Fourier transform.

245. The method of embodiment 244, wherein an existence of the one ormore correlations provides an indication of the presence of the fluid inthe subterranean formation.

246. The method of embodiment 244 or 245, wherein the one or morecorrelations indicate one or more transit times between the subterraneanformation and the surface of the earth.

247. The method of embodiment 246, further comprising correlating theone or more transit times to a depth of the fluid in the subterraneanformation.

248. The method of embodiment 247, wherein the correlating is based onestimate rock acoustic properties of the earth.

249. The method of embodiment 247 or 248, wherein correlating comprisesdetermining a frequency-depth relationship.

250. The method of embodiment 249, wherein the frequency-depthrelationship is determined based on a classification method comprisingat least one method selected from the group consisting of: a neuralnetwork, a decision tree, a Bayes-based classifier, a fuzzy logic-basedclassifier, and a conventional statistical classifier.

251. The method of embodiment 249 or 250, wherein the frequency-depthrelationship is determined based on a regression analysis of a set ofknown empirical data.

252. The method of any of embodiments 214 to 251, further comprisingperforming a correlation analysis of the detected seismic signal in thetime domain, the frequency domain, or both, wherein the correlationanalysis provides an indication of a presence of the at least one fluid.

253. The method of embodiment 252, wherein performing the correlationanalysis provides at least one of temporal characteristics or frequencycharacteristics.

254. The method of embodiment 253, further comprising deriving afrequency-depth function based on the temporal characteristics, thefrequency characteristics, or both.

255. The method of embodiment 254, wherein the frequency-depth functionis derived using data from a known location.

256. The method of any of embodiments 214 to 255, further comprisingrepeating the passively detecting, and processing a plurality of times.

257. The method of embodiment 256, wherein the repeating is performed ata single location.

258. The method of embodiment 256, wherein the repeating is performed atdifferent locations.

259. The method of embodiment 258, wherein the repeating is performedsequentially or concurrently at each of the different locations.

260. The method of embodiment 258 or 259, wherein the differentlocations correspond to a plurality of grid positions.

261. The method of embodiment 260, further comprising generating amulti-dimension model of a subterranean formation using a plurality ofdetected seismic signals, wherein at least one signal of the pluralityof detected seismic signals is determined at each corresponding gridposition of the plurality of grid positions.

262. The method of any of embodiments 214 to 261, further comprising:performing a further survey of the subterranean formation when apresence of the at least one fluid is detected.

263. The method of embodiment 262, wherein the further survey comprisesa seismological survey, a controlled-source electromagnetics survey, acontrolled-source electroseismic survey, a controlled-sourceseismoelectric survey, a gravity survey, a magnetic survey, or a passivesurvey.

264. The method of any of embodiments 214 to 263, further comprising:developing a geological model of the subsurface earth formation;determining at least one predicted result from the geological model;comparing the at least one predicted result to the detected seismicsignal; and determining the at least one property of the subsurfaceearth formation based on the comparing.

265. The method of any of embodiments 214 to 264, wherein generating theone or more detected signals further comprises: generating at least onenonlinear seismic signal by isolating the at least one nonlinear seismicsignal from the detected seismic signal; and wherein processing the oneor more detected signals further comprises: processing the at least onenonlinear seismic signal to determine at least one property of thesubsurface earth formation.

266. In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: one or more sensors coupled to aprocessor that detect one or more signals generated within a subsurfaceearth formation due to a seismoelectric response or an electroseismicresponse in at least one porous subsurface earth formation containing atleast one fluid; and an analysis tool, that when executed on theprocessor, configures the processor to: receive the one or more signalsfrom the one or more sensors; process at least a portion of the one ormore signals to determine at least one property of the subsurface earthformation.

267. The system of embodiment 266, wherein the one or more sensorscomprise a plurality of seismic sensors that detect a seismic signalrelated to earth's electromagnetic field and produce a first signalindicative of the detected seismic signal, and wherein the analysis toolreceives the first signal and processes the first signal to determinethe at least one property of the subsurface earth formation.

268. The system of embodiment 267, wherein the plurality of seismicsensors is arranged in an array over a portion of the subsurface earthformation.

269. The system of embodiment 267 or 268, wherein the distance betweeneach of the plurality of seismic sensors is less than one half of thewavelength of the surface waves at an expected surface wave frequency.

270. The system of any of embodiments 267 to 269, wherein the pluralityof seismic sensors comprises at least one sensor selected from the groupconsisting of: a hydrophone, a single-component geophone, atwo-component geophone, a three-component geophone, a single-axisaccelerometer, a two-axis accelerometer, a three-axis accelerometer, andany combination thereof.

271. The system of any of embodiments 267 to 270, wherein the at leastone property of the subsurface earth formation comprises at least oneproperty selected from the group consisting of: an existence of thesubsurface earth formation containing at least one fluid, a depth of thesubsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof.

272. The system of any of embodiments 267 to 271, further comprising arecording apparatus configured to record the first signal on anon-transitory media.

273. The system of any of embodiments 267 to 272, wherein the at leastone fluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

274. The method of embodiment 273, wherein the aqueous fluid comprisesat least one of potable water, fresh water, or brine.

275. The system of any of embodiments 267 to 274, wherein at least oneof the plurality of seismic sensors is disposed on the surface of theearth or within a wellbore.

276. The system of any of embodiments 267 to 275, wherein the analysistool further configures the processor to: decimate a data setrepresenting the first signal.

277. The system of any of embodiments 267 to 276, wherein the analysistool further configures the processor to: filter a noise component fromthe first signal.

278. The system of any of embodiments 267 to 277, wherein the analysistool further configures the processor to: filter the first signal usinga predetermined frequency bandwidth.

279. In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: a memory comprising a non-transitorycomputer readable media; a processor; and an analysis tool, that whenexecuted on the processor, configures the processor to: receive one ormore signals from one or more sensors, wherein the one or more sensorsdetect one or more signals generated within a subsurface earth formationdue to a seismoelectric response or an electroseismic response in atleast one porous subsurface earth formation containing at least onefluid; and process at least a portion of the one or more signals todetermine at least one property of the subsurface earth formation.

280. The system of embodiment 279, wherein the one or more sensorscomprise a plurality of seismic sensors that detect a seismic signalrelated to earth's electromagnetic field and produce a first signalindicative of the detected seismic signal, and wherein the analysis toolconfigures the processor to receive the first signal, and process thefirst signal to determine the at least one property of the subsurfaceearth formation.

281. In an embodiment, a method of passive surveying comprises:generating one or more detected signals by passively detecting a signalgenerated within a subsurface earth formation due to a seismoelectricresponse or an electroseismic response in at least one porous subsurfaceearth formation containing at least one fluid; and processing the one ormore detected signals to determine at least one property of thesubsurface earth formation.

282. The method of embodiment 281, wherein generating the one or moredetected signals comprises: generating a detected electromagnetic fieldby detecting earth's electromagnetic field using an electromagneticfield detector; and generating a detected seismic signal by detecting aseismic wave at least partially resulting from the electroseismicresponse in the at least one porous subsurface earth formationcontaining the at least one fluid using a seismic sensor; and whereinprocessing the one or more detected signals comprises: processing thedetected electromagnetic field and the detected seismic signal todetermine the at least one property of the subsurface earth formation.

283. The method of embodiment 282, wherein the detected electromagneticfield is generated at a different time than the detected seismic signal.

284. The method of embodiment 282 or 283, wherein the detectedelectromagnetic field is generated at a different location than thedetected seismic signal.

285. The method of any of embodiments 282 to 284, wherein detecting theearth's electromagnetic field comprises measuring a vertical electriccomponent of the earth's electromagnetic field.

286. The method of embodiment 285, further comprising generating adetected magnetic field by detecting earth's magnetic field using amagnetic field detector, and processing the detected magnetic field withthe vertical electric component and the detected seismic signal.

287. The method of any of embodiments 282 to 286, wherein detecting theearth's electromagnetic field comprises measuring the earth'selectromagnetic field in at least one horizontal direction.

288. The method of any of embodiments 282 to 287, wherein the earth'selectromagnetic field comprises a time-varying electromagnetic field.

289. The method of any of embodiments 282 to 288, wherein the earth'selectromagnetic field is detected using a pair of porous pot electrodes.

290. The method of embodiment 289, wherein the pair of porous potelectrodes comprises at least one component selected from the groupconsisting of: copper sulfate, silver chloride, cadmium chloride,mercury chloride, and lead chloride.

291. The method of any of embodiments 282 to 290, wherein the earth'selectromagnetic field is detected using a plurality of pairs of porouspot electrodes.

292. The method of any of embodiments 282 to 291, wherein the earth'selectromagnetic field is detected using a pair of conductive electrodes.

293. The method of embodiment 292, wherein the pair of metal electrodescomprises at least one conductive material selected from the groupconsisting of: copper, stainless steel, aluminum, gold, galvanizedmetal, iron, lead, brass, graphite, and steel.

294. The method of any of embodiments 282 to 293, wherein the earth'selectromagnetic field is detected using a conductive electrode coupledto a porous pot electrode.

295. The method of any of embodiments 282 to 294, wherein theelectromagnetic field detector is disposed on or above the surface ofthe earth.

296. The method of any of embodiments 282 to 295, wherein theelectromagnetic field detector is moving during the generation of thedetected electromagnetic field.

297. The method of any of embodiments 282 to 296, wherein theelectromagnetic field detector is disposed in a moving vehicle.

298. The method of any of embodiments 282 to 297, wherein the detectedelectromagnetic field is generated using one or more antennas disposedon or above a surface of the earth.

299. The method of embodiment 298, wherein the one or more antennascomprises at least one antenna selected from the group consisting of: aparallel-plate capacitor antenna comprising two or more parallelconducting plates, a single-plate capacitor antenna comprising oneelectrode electrically coupled to the earth, a monopole antennacomprising a conducting element, a dipole antenna comprising twoconducting elements, a multi-pole antenna comprising a plurality ofconducting elements, a directional antenna comprising conductingelements arranged to augment a signal amplitude in a particulardirection, a coil antenna comprising one or more coils of wire, and anycombination thereof.

300. The method of embodiment 298, wherein the one or more antennascomprise a concentric electric dipole.

301. The method of any of embodiments 282 to 300, wherein the seismicsensor comprises at least one sensor selected from the group consistingof: a hydrophone, a single-component geophone, a two-component geophone,a three-component geophone, a single-axis accelerometer, a two-axisaccelerometer, and a three-axis accelerometer.

302. The method of any of embodiments 282 to 301, wherein the at leastone property of the subsurface earth formation comprises at least oneproperty selected from the group consisting of: an existence of thesubsurface earth formation containing at least one fluid, a depth of thesubsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof.

303. The method of any of embodiments 282 to 302, further comprisingrecording at least one of the detected electromagnetic field or thedetected seismic signal.

304. The method of embodiment 303, wherein the recording occurs for atleast about 5 seconds.

305. The method of embodiment 303, wherein the modulated referencesignal is recorded for at least about 0.1 seconds.

306. The method of any of embodiments 282 to 305, wherein the at leastone fluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

307. The method of embodiment 306, wherein the aqueous fluid comprisesat least one of potable water, fresh water, or brine.

308 The method of any of embodiments 282 to 307, wherein the detectedelectromagnetic field results, at least in part, from a natural eventcomprising at least one of: an electromagnetic fluctuation in theionosphere, and a naturally occurring electric discharge in theatmosphere.

309. The method of any of embodiments 282 to 308, wherein the seismicwave is detected on the surface of the earth.

310. The method of any of embodiments 282 to 309, wherein the seismicwave is detected within a wellbore.

311. The method of any of embodiments 282 to 310, further comprising aplurality of electromagnetic field detectors.

312. The method of embodiment 311, wherein the plurality ofelectromagnetic field detectors are arranged in an array.

313. The method of any of embodiments 282 to 312, further comprising aplurality of seismic sensors.

314. The method of embodiment 313, wherein the plurality of seismicsensors are arranged in an array over a portion of the subsurface earthformation.

315. The method of embodiment 313 or 314, wherein processing thedetected electromagnetic field and the detected seismic signalcomprises: filtering at least a portion of a seismic wave traveling in adirection perpendicular to vertical by applying a spatial filter to thedetected seismic signal from the plurality of seismic sensors.

316. The method of embodiment 315, wherein the spatial filter is based,at least in part, on the spreading symmetry of the seismic wavetraveling in the direction perpendicular to vertical.

317. The method of any of embodiments 313 to 316, wherein processing thedetected electromagnetic field and the detected seismic signalcomprises: removing a seismic noise from a vertical component of thedetected seismic signal by applying a predictive filter to the detectedseismic signal based on using a horizontal component of the detectedseismic signal from the plurality of seismic sensors.

318. The method of any of embodiments 313 to 317, wherein processing thedetected electromagnetic field and the detected seismic signalcomprises: applying a dip filter to the detected seismic signal based onrejecting at least a portion of the detected seismic signals from theplurality of seismic sensors that arrive at a non-normal angle to asurface, wherein the surface is defined by the plurality of seismicsensors.

319. The method of any of embodiments 313 to 318, wherein processing thedetected electromagnetic field and the detected seismic signalcomprises: producing cross-correlated seismic data by cross-correlatingthe detected seismic signal from all of the plurality of seismicsensors; generating summed data by summing the cross-correlated seismicdata; and cross-correlating the summed data with the detectedelectromagnetic field.

320. The method of any of embodiments 282 to 319, further comprisingperforming a correlation analysis of at least one of the detectedelectromagnetic field or the detected seismic signal in the time domain,the frequency domain, or both, wherein the correlation analysis providesan indication of a presence of the at least one fluid.

321. The method of embodiment 320, wherein performing the correlationanalysis provides at least one of temporal characteristics or frequencycharacteristics.

322. The method of embodiment 321, further comprising deriving afrequency-depth function based on the temporal characteristics, thefrequency characteristics, or both.

323. The method of embodiment 322, wherein the frequency-depth functionis derived using data from a known location.

324. The method of any of embodiments 282 to 323, further comprisingrepeating the passively detecting, and processing a plurality of times.

325. The method of embodiment 324, wherein the repeating is performed ata single location.

326. The method of embodiment 324, wherein the repeating is performed atdifferent locations.

327. The method of embodiment 326, wherein the repeating is performedsequentially or concurrently at each of the different locations.

328. The method of embodiment 326 or 327, wherein the differentlocations correspond to a plurality of grid positions.

329. The method of embodiment 328, further comprising generating amulti-dimension model of a subterranean formation using a plurality ofsignals, wherein at least one signal of the plurality of signals isdetermined at each corresponding grid position of the plurality of gridpositions.

330. The method of any of embodiments 282 to 329, further comprising:performing a further survey of the subterranean formation when apresence of the at least one fluid is detected.

331. The method of embodiment 330, wherein the further survey comprisesa seismological survey, a controlled-source electromagnetics survey, acontrolled-source electroseismic survey, a controlled-sourceseismoelectric survey, a gravity survey, a magnetic survey, or a passivesurvey.

332. The method of any of embodiments 282 to 331, wherein processing theone or more detected signals further comprises: filtering at least oneof the detected electromagnetic field or the detected seismic signal.

333. The method of embodiment 332, wherein the filtering and processingoccur in real time.

334. The method of embodiment 332 or 333, wherein filtering comprisesfiltering a direct current (DC) portion of the detected electromagneticfield prior to performing the processing.

335. The method of any of embodiments 332 to 334, wherein filteringcomprises decimating a data set representing the signal prior toperforming the processing.

336. The method of any of embodiments 332 to 335, wherein filteringcomprises using a noise filter.

337. The method of embodiment 336, wherein the noise filter comprises ahigh pass filter, a low pass filter, a wide band frequency filter, anarrow band frequency filter, or any combination thereof.

338. The method of any of embodiments 332 to 337, wherein filteringcomprises using one or more band-pass filters.

339. The method of embodiment 338, wherein at least one of the band-passfilters of the one or more band-pass filters comprises a linear phasefilter, a finite impulse response filter, a forward infinite impulseresponse filter, a reverse infinite impulse response filter, or anycombination thereof.

340. The method of any of embodiments 282 to 339, wherein processing thedetected electromagnetic field and the detected seismic signal comprisesaveraging an amplitude of at least one of the detected electromagneticfield or the detected seismic signal over one or more frequencies.

341. The method of embodiment 340, wherein the plurality of frequenciescomprises one or more fixed frequencies.

342. The method of embodiment 340 or 341, wherein the averagingcomprises measuring an amplitude of the at least one of the detectedelectromagnetic field or the detected seismic signal for a length oftime that is greater than a period of oscillation of the at least one ofthe detected electromagnetic field or the detected seismic signal at theone or more frequencies; and averaging the amplitude over the length oftime.

343. The method of any of embodiments 282 to 342, wherein processing atleast one of the detected electromagnetic field or the detected seismicsignal comprises determining one or more spectral properties of the atleast one of the detected electromagnetic field or the detected seismicsignal.

344. The method of embodiment 343, wherein determining one or morespectral properties comprises using at least one of a lock-in amplifieror a spectrum analyzer.

345. The method of embodiment 343 or 344, wherein determining one ormore spectral properties comprises determining a relative amplitude ofeach frequency at which an amplitude is determined.

346. The method of any of embodiments 343 to 345, further comprisinganalyzing the one or more spectral properties to determine arelationship between the one or more spectral properties and thepresence of the at least one fluid in the subterranean formation basedon a classification method comprising at least one method selected fromthe group consisting of: a neural network, a decision tree, aBayes-based classifier, a fuzzy logic-based classifier, and aconventional statistical classifier.

347. The method of any of embodiments 343 to 346, further comprisinganalyzing the one or more spectral properties to determine arelationship between the one or more spectral properties and a presenceof the at least one fluid in the subterranean formation based on aregression analysis of a set of known empirical data.

348. The method of any of embodiments 343 to 347, wherein determiningone or more spectral properties comprises calculating one or more powerspectral densities.

349. The method of embodiment 348, further comprising de-trending of theone or more power spectral densities.

350. The method of embodiment 348 or 349, further comprising integratingeach of the one or more power spectral densities.

351. The method of any of embodiments 348 to 350, further comprisingperforming a fast Fourier transform of the one or more power spectraldensities; and determining one or more correlations between a sourcesignal and the at least one of the detected electromagnetic field or thedetected seismic signal based on the fast Fourier transform.

352. The method of embodiment 351, wherein an existence of the one ormore correlations provides an indication of the presence of the at leastone fluid in the subterranean formation.

353. The method of embodiment 351 or 352, wherein the one or morecorrelations indicate one or more transit times between the subterraneanformation and the surface of the earth.

354. The method of embodiment 353, further comprising correlating theone or more transit times to a depth of the fluid in the subterraneanformation.

355. The method of embodiment 354, wherein the correlating is based onestimate rock acoustic properties of the earth.

356. The method of embodiment 354 or 355, wherein correlating comprisesdetermining a frequency-depth relationship.

357. The method of embodiment 356, wherein the frequency-depthrelationship is determined based on a classification method comprisingat least one method selected from the group consisting of: a neuralnetwork, a decision tree, a Bayes-based classifier, a fuzzy logic-basedclassifier, and a conventional statistical classifier.

358. The method of embodiment 356 or 357, wherein the frequency-depthrelationship is determined based on a regression analysis of a set ofknown empirical data.

359. The method of any of embodiments 282 to 358, further comprising:developing a geological model of the subsurface earth formation;determining at least one predicted result from the geological model;comparing the at least one predicted result to at least one of thedetected electromagnetic field or the detected seismic signal; anddetermining the at least one property of the subsurface earth formationbased on the comparing.

360. In an embodiment, a method comprises: generating a detectedelectromagnetic field by detecting earth's electromagnetic field usingat least one electromagnetic field detector in the earth; generating adetected seismic signal by detecting a seismic wave related to theearth's electromagnetic field using a seismic sensor, wherein thedetected electromagnetic field is generated at a different time, adifferent location, or both than the detected seismic signal; generatinga detected noise signal by detecting at least one background noisecomponent; filtering the detected electromagnetic field, the detectedseismic signal, or both using the detected noise signal to provide afiltered signal, wherein the filtered signal comprises the detectedelectromagnetic field, the detected seismic signal, or both having anincreased signal to noise ratio; and processing the filtered signal andthe detected electromagnetic field, the detected seismic signal, or bothto determine at least one property of the subsurface earth formation.

361. The method of embodiment 360, wherein the background noisecomponent comprises a background electromagnetic field.

362. The method of embodiment 361, wherein the detected noise signal isgenerated with an electromagnetic field detector on or above the surfaceof the earth.

363. The method of embodiment 361 or 362, wherein the detected noisesignal is generated by cross-correlating the signal from the at leastone electromagnetic field detector in the earth.

364. The method of any of embodiments 361 to 363, wherein the detectednoise signal is generated by an electromagnetic field detector capableof measuring at least one horizontal electromagnetic field component inthe earth.

365. The method of any of embodiments 361 to 364, wherein the detectednoise signal is generated with an electromagnetic field sensor on orabove a surface of the earth and distanced from the at least oneelectromagnetic field detector in the earth.

366. The method of any of embodiments 361 to 365, wherein the detectednoise signal comprises a background seismic signal at the surface of theearth.

367. The method of any of embodiments 361 to 366, wherein the detectednoise signal is generated using a plurality of seismic sensors.

368. In an embodiment, a method comprising: generating a detectedelectromagnetic field by detecting earth's electromagnetic field usingat least one electromagnetic field detector; generating a detectedseismic signal by detecting a seismic wave related to the earth'selectromagnetic field using a seismic sensor, wherein the detectedelectromagnetic field is generated at a different time, a differentlocation, or both than the detected seismic signal; isolating at leastone nonlinear electromagnetic field response from the detectedelectromagnetic field; and processing the at least one nonlinearelectromagnetic field and the detected seismic signal to determine atleast one property of the subsurface earth formation.

369. The method of embodiment 368, wherein isolating at least onenonlinear seismic signal comprises: identifying fundamental frequenciespresent in the detected electromagnetic field by cross-correlating thedetected electromagnetic field and a detected distant electromagneticfield generated by a distant electromagnetic field detector located atleast 500 yards from the at least one electromagnetic field detector;and identifying the at least one nonlinear electromagnetic fieldresponse by filtering the fundamental frequencies from the detectedelectromagnetic field.

370. The method of embodiment 368, wherein isolating at least onenonlinear seismic signal comprises: identifying fundamental frequenciespresent in the detected electromagnetic field by cross-correlating thedetected electromagnetic field and a detected atmosphericelectromagnetic field generated by an atmospheric electromagnetic fielddetector located above the surface of the earth; and identifying the atleast one nonlinear electromagnetic field response by filtering thefundamental frequencies from the detected electromagnetic field.

371. In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: one or more sensors coupled to aprocessor that detect one or more signals generated within a subsurfaceearth formation due to a seismoelectric response or an electroseismicresponse in at least one porous subsurface earth formation containing atleast one fluid; and an analysis tool, that when executed on theprocessor, configures the processor to: receive the one or more signalsfrom the one or more sensors; process at least a portion of the one ormore signals to determine at least one property of the subsurface earthformation.

372. The system of embodiment 371, wherein the one or more sensorscomprise: a plurality of seismic sensors that detects a seismic signalrelated to earth's electromagnetic field and produce a first signalindicative of the detected seismic signal; an electromagnetic fielddetector that measures the earth's electromagnetic field and produces asecond signal indicative of the detected electromagnetic field; andwherein the analysis tool receives the first signal and the secondsignal and determines the at least one property of a subsurface earthformation.

373. The system of embodiment 372, wherein the first signal is generatedat a different time than the second signal.

374. The system of embodiment 373, wherein the first signal is generatedat a different location than the second signal.

375. The system of any of embodiments 372 to 374, wherein the pluralityof seismic sensors are arranged in an array over a portion of thesubsurface earth formation.

376. The system of any of embodiments 372 to 375, wherein theelectromagnetic field detector is disposed within the surface of theearth below the plurality of seismic sensors.

377. The system of any of embodiments 372 to 376, wherein the distancebetween each of the plurality of seismic sensors is less than one halfof the wavelength of the surface waves at an expected surface wavefrequency.

378. The system of any of embodiments 372 to 377, further comprising aplurality of electromagnetic field detectors.

379. The system of any of embodiments 372 to 378, wherein the secondsignal comprises a vertical component of the earth's electromagneticfield.

380. The system of any of embodiments 372 to 379, wherein the secondsignal comprises at least one horizontal component of the earth'selectromagnetic field.

381. The system of any of embodiments 372 to 380, wherein the secondsignal is indicative of a time-varying electromagnetic field.

382. The system of any of embodiments 372 to 381, wherein theelectromagnetic field detector comprises a plurality of pairs of porouspot electrodes, wherein each pair of porous pot electrodes areelectrically coupled.

383. The system of embodiment 382, wherein the pairs of porous potelectrodes comprise at least one component selected from the groupconsisting of: copper sulfate, silver chloride, cadmium chloride,mercury chloride, and lead chloride.

384. The system of any of embodiments 372 to 383, wherein theelectromagnetic field detector comprises a plurality of pairs ofconductive electrodes, wherein each pair of conductive electrodes areelectrically coupled.

385. The system of any of embodiments 372 to 384, wherein the pluralityof conductive electrodes comprises at least one conductive materialselected from the group consisting of: copper, stainless steel,aluminum, gold, galvanized metal, iron, lead, brass, graphite, steel,alloys thereof, and any combination thereof.

386. The system of any of embodiments 372 to 385, wherein theelectromagnetic field detector comprises a conductive electrode coupledto a porous pot electrode.

387. The system of any of embodiments 372 to 386, wherein the pluralityof seismic sensors comprises at least one sensor selected from the groupconsisting of: a hydrophone, a single-component geophone, atwo-component geophone, a three-component geophone, a single-axisaccelerometer, a two-axis accelerometer, a three-axis accelerometer, andany combination thereof.

388. The system of any of embodiments 372 to 387, wherein the at leastone property of the subsurface earth formation comprises at least oneproperty selected from the group consisting of: an existence of thesubsurface earth formation containing at least one fluid, a depth of thesubsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof.

389. The system of any of embodiments 372 to 388, further comprising arecording apparatus configured to record the first signal and the secondsignal on a non-transitory media.

390. The system of embodiment 389, wherein the recording apparatuscomprises a digital or analog recording device.

391. The system of any of embodiments 372 to 390, wherein the at leastone fluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

392. The system of embodiment 391, wherein the aqueous fluid comprisesat least one of potable water, fresh water, or brine.

393. The system of any of embodiments 372 to 392, wherein at least oneof the plurality of seismic sensors is disposed on the surface of theearth or within a wellbore.

394. The system of any of embodiments 372 to 393, wherein at least oneof the plurality of seismic sensors is disposed within a wellbore.

395. The system of any of embodiments 372 to 394, wherein theelectromagnetic field detector comprises an antenna disposed on or abovethe surface of the earth.

396. The system of embodiment 395, wherein the antenna comprises atleast one antenna selected from the group consisting of: aparallel-plate capacitor antenna comprising two or more parallelconducting plates, a single-plate capacitor antenna comprising oneelectrode electrically coupled to the earth, a monopole antennacomprising a conducting element, a dipole antenna comprising twoconducting elements, a multi-pole antenna comprising a plurality ofconducting elements, a directional antenna comprising conductingelements arranged to augment a signal amplitude in a particulardirection, a coil antenna comprising one or more coils of wire, and anycombination thereof.

397. The system of embodiment 395, wherein the antenna comprises aconcentric electric dipole.

398. The system of any of embodiments 372 to 397, wherein the analysistool further configures the processor to: remove a direct current (DC)portion of the second signal.

399. The system of embodiment 272, wherein the analysis tool furtherconfigures the processor to: decimate a data set representing at leastone of the first signal or second signal.

400. The system of any of embodiments 372 to 399, wherein the analysistool further configures the processor to: filter a noise component fromat least one of the first signal or second signal.

401. The system of any of embodiments 372 to 400, wherein the analysistool further configures the processor to: filter at least one of thefirst signal or second signal using a predetermined frequency bandwidth.

402. In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: a memory comprising a non-transitorycomputer readable media; a processor; and an analysis tool, that whenexecuted on the processor, configures the processor to: receive one ormore signals from one or more sensors, wherein the one or more sensorsdetect one or more signals generated within a subsurface earth formationdue to a seismoelectric response or an electroseismic response in atleast one porous subsurface earth formation containing at least onefluid; and process at least a portion of the one or more signals todetermine at least one property of the subsurface earth formation.

403. The system of embodiment 402, wherein the one or more sensorscomprise a plurality of seismic sensors that detects a seismic signalrelated to earth's electromagnetic field and produce a first signalindicative of the detected seismic signal, and an electromagnetic fielddetector that measures the earth's electromagnetic field and produces asecond signal indicative of the detected electromagnetic field; andwherein the analysis tool further configures the processor to receivethe first signal and the second signal, and determine the at least oneproperty of a subsurface earth formation.

404. In an embodiment, a method of passive surveying comprises:generating one or more detected signals by passively detecting a signalgenerated within a subsurface earth formation due to a seismoelectricresponse or an electroseismic response in at least one porous subsurfaceearth formation containing at least one fluid; and processing the one ormore detected signals to determine at least one property of thesubsurface earth formation.

405. The method of embodiment 404, wherein generating the one or moredetected signals comprises: generating a detected electromagnetic fieldby detecting earth's electromagnetic field using an electromagneticfield detector; and generating a detected seismic signal by detecting aseismic wave at least partially resulting from the electroseismicresponse in the at least one porous subsurface earth formationcontaining the at least one fluid using a seismic sensor; and whereinprocessing the one or more detected signals comprises: processing thedetected electromagnetic field and the detected seismic signal todetermine the at least one property of the subsurface earth formation.

406. The method of embodiment 405, wherein detecting the earth'selectromagnetic field comprises measuring a vertical electric componentof the earth's electromagnetic field.

407. The method of embodiment 406, further comprising generating adetected magnetic field by detecting earth's magnetic field using amagnetic field detector, and processing the detected magnetic field withthe vertical electric component and the detected seismic signal.

408. The method of any of embodiments 405 to 407, wherein detecting theearth's electromagnetic field comprises measuring the earth'selectromagnetic field in at least one horizontal direction.

409. The method of any of embodiments 405 to 408, wherein the earth'selectromagnetic field comprises a time-varying electromagnetic field.

410. The method of any of embodiments 405 to 409, wherein the earth'selectromagnetic field is detected using a pair of porous pot electrodes.

411. The method of embodiment 410, wherein the pair of porous potelectrodes comprises at least one component selected from the groupconsisting of: copper sulfate, silver chloride, cadmium chloride,mercury chloride, and lead chloride.

412. The method of any of embodiments 405 to 411, wherein the earth'selectromagnetic field is detected using a plurality of pairs of porouspot electrodes.

413. The method of any of embodiments 405 to 412, wherein the earth'selectromagnetic field is detected using a pair of conductive electrodes.

414. The method of embodiment 413, wherein the pair of metal electrodescomprises at least one conductive material selected from the groupconsisting of: copper, stainless steel, aluminum, gold, galvanizedmetal, iron, lead, brass, graphite, and steel.

415. The method of any of embodiments 405 to 414, wherein the earth'selectromagnetic field is detected using a conductive electrode coupledto a porous pot electrode.

416. The method of any of embodiments 405 to 415, wherein theelectromagnetic field detector is disposed on or above the surface ofthe earth.

417. The method of any of embodiments 405 to 416, wherein theelectromagnetic field detector is moving during the generation of thedetected electromagnetic field.

418. The method of any of embodiments 405 to 417, wherein theelectromagnetic field detector is disposed in a moving vehicle.

419. The method of any of embodiments 405 to 418, wherein the detectedelectromagnetic field is generated using one or more antennas disposedon or above a surface of the earth.

420. The method of embodiment 419, wherein the one or more antennascomprises at least one antenna selected from the group consisting of: aparallel-plate capacitor antenna comprising two or more parallelconducting plates, a single-plate capacitor antenna comprising oneelectrode electrically coupled to the earth, a monopole antennacomprising a conducting element, a dipole antenna comprising twoconducting elements, a multi-pole antenna comprising a plurality ofconducting elements, a directional antenna comprising conductingelements arranged to augment a signal amplitude in a particulardirection, a coil antenna comprising one or more coils of wire, and anycombination thereof.

421. The method of embodiment 419, wherein the one or more antennascomprise a concentric electric dipole.

422. The method of any of embodiments 405 to 421, wherein the seismicsensor comprises at least one sensor selected from the group consistingof: a hydrophone, a single-component geophone, a two-component geophone,a three-component geophone, a single-axis accelerometer, a two-axisaccelerometer, and a three-axis accelerometer.

423. The method of any of embodiments 405 to 422, wherein the at leastone property of the subsurface earth formation comprises at least oneproperty selected from the group consisting of: an existence of thesubsurface earth formation containing at least one fluid, a depth of thesubsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof.

424. The method of any of embodiments 405 to 423, further comprisingrecording at least one of the detected electromagnetic field or thedetected seismic signal.

425. The method of embodiment 424, wherein the recording occurs for atleast about 5 seconds.

426. The method of embodiment 424, wherein the modulated referencesignal is recorded for at least about 0.1 seconds.

427. The method of any of embodiments 405 to 426, wherein the at leastone fluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

428. The method of embodiment 427, wherein the aqueous fluid comprisesat least one of potable water, fresh water, or brine.

429. The method of any of embodiments 405 to 428, wherein the detectedelectromagnetic field results, at least in part, from a natural eventcomprising at least one of: an electromagnetic fluctuation in theionosphere, and a naturally occurring electric discharge in theatmosphere.

430. The method of any of embodiments 405 to 429, wherein the seismicwave is detected on the surface of the earth.

431. The method of any of embodiments 405 to 430, wherein the seismicwave is detected within a wellbore.

432. The method of any of embodiments 405 to 431, wherein processing thedetected electromagnetic field and the detected seismic signalcomprises: cross-correlating the detected electromagnetic field with thedetected seismic signal; and isolating at least a portion of thedetected seismic signal arising from the conversion of the earth'selectromagnetic field to seismic energy.

433. The method of any of embodiments 405 to 432, further comprising aplurality of electromagnetic field detectors.

434. The method of embodiment 433, wherein the plurality ofelectromagnetic field detectors are arranged in an array.

435. The method of any of embodiments 405 to 434, further comprising aplurality of seismic sensors.

436. The method of embodiment 435, wherein the plurality of seismicsensors are arranged in an array over a portion of the subsurface earthformation.

437. The method of embodiment 435 or 436, wherein processing thedetected electromagnetic field and the detected seismic signalcomprises: filtering at least a portion of a seismic wave traveling in adirection perpendicular to vertical by applying a spatial filter to thedetected seismic signal from the plurality of seismic sensors.

438. The method of any of embodiments 435 to 437, wherein the spatialfilter is based, at least in part, on the spreading symmetry of theseismic wave traveling in the direction perpendicular to vertical.

439. The method of any of embodiments 435 to 438, wherein processing thedetected electromagnetic field and the detected seismic signalcomprises: removing a seismic noise from a vertical component of thedetected seismic signal by applying a predictive filter to the detectedseismic signal based on using a horizontal component of the detectedseismic signal from the plurality of seismic sensors.

440. The method of any of embodiments 435 to 439, wherein processing thedetected electromagnetic field and the detected seismic signalcomprises: applying a dip filter to the detected seismic signal based onrejecting at least a portion of the detected seismic signals from theplurality of seismic sensors that arrive at a non-normal angle to asurface, wherein the surface is defined by the plurality of seismicsensors.

441. The method of any of embodiments 435 to 440, wherein processing thedetected electromagnetic field and the detected seismic signalcomprises: producing cross-correlated seismic data by cross-correlatingthe detected seismic signal from all of the plurality of seismicsensors; generating summed data by summing the cross-correlated seismicdata; and cross-correlating the summed data with the detectedelectromagnetic field.

442. The method of any of embodiments 405 to 441, further comprisingperforming a correlation analysis of at least one of the detectedelectromagnetic field or the detected seismic signal in the time domain,the frequency domain, or both, wherein the correlation analysis providesan indication of a presence of the at least one fluid.

443. The method of embodiment 442, wherein performing the correlationanalysis provides at least one of temporal characteristics or frequencycharacteristics.

444. The method of embodiment 443, further comprising deriving afrequency-depth function based on the temporal characteristics, thefrequency characteristics, or both.

445. The method of embodiment 444, wherein the frequency-depth functionis derived using data from a known location.

446. The method of any of embodiments 405 to 445, further comprisingrepeating the passively detecting, and processing a plurality of times.

447. The method of embodiment 446, wherein the repeating is performed ata single location.

448. The method of embodiment 446, wherein the repeating is performed atdifferent locations.

449. The method of embodiment 448, wherein the repeating is performedsequentially or concurrently at each of the different locations.

450. The method of embodiment 448 or 449, wherein the differentlocations correspond to a plurality of grid positions.

451. The method of embodiment 450, further comprising generating amulti-dimension model of a subterranean formation using a plurality ofsignals, wherein at least one signal of the plurality of signals isdetermined at each corresponding grid position of the plurality of gridpositions.

452. The method of any of embodiments 405 to 451, further comprising:performing a further survey of the subterranean formation when apresence of the at least one fluid is detected.

453. The method of embodiment 452, wherein the further survey comprisesa seismological survey, a controlled-source electromagnetics survey, acontrolled-source electroseismic survey, a controlled-sourceseismoelectric survey, a gravity survey, a magnetic survey, or a passivesurvey.

454. The method of any of embodiments 405 to 453, wherein processing theone or more detected signals further comprises: filtering at least oneof the detected electromagnetic field or the detected seismic signal.

455. The method of embodiment 454, wherein the filtering and processingoccur in real time.

456. The method of embodiment 454 or 455, wherein filtering comprisesfiltering a direct current (DC) portion of the detected electromagneticfield prior to performing the processing.

457. The method of any of embodiments 454 to 456, wherein filteringcomprises decimating a data set representing the signal prior toperforming the processing.

458. The method of any of embodiments 454 to 457, wherein filteringcomprises using a noise filter.

459. The method of embodiment 458, wherein the noise filter comprises ahigh pass filter, a low pass filter, a wide band frequency filter, anarrow band frequency filter, or any combination thereof.

460. The method of any of embodiments 454 to 459, wherein filteringcomprises using one or more band-pass filters.

461. The method of embodiment 460, wherein at least one of the band-passfilters of the one or more band-pass filters comprises a linear phasefilter, a finite impulse response filter, a forward infinite impulseresponse filter, a reverse infinite impulse response filter, or anycombination thereof.

462. In an embodiment, a method comprises: generating a detectedelectromagnetic field by detecting earth's electromagnetic field;generating a detected seismic signal by detecting a seismic wave relatedto the earth's electromagnetic field; generating a first signal byadding a plurality of intervals of the detected electromagnetic field,wherein each of the plurality of intervals of the detectedelectromagnetic field begins at a start time and continues for aduration; and generating a second signal by adding a plurality ofintervals of the detected seismic signal corresponding to the pluralityof intervals of the detected electromagnetic field, wherein each of theplurality of intervals of the detected seismic signals begins at thestart time of the corresponding interval of the detected electromagneticfield and continues for the duration of the corresponding interval ofthe detected electromagnetic field; determining at least one property ofthe subsurface earth formation by processing the first signal and thesecond signal.

463. The method of embodiment 462, wherein the number of the pluralityof intervals of the detected electromagnetic field and the number of theplurality of intervals of the detected seismic signal are chosen toproduce a predetermined signal to noise ratio.

464. The method of embodiment 462 or 463, wherein at least one starttime corresponds to the zero crossing voltage of a coherent noisesource.

465. The method of any of embodiments 462 to 464, wherein at least onestart time corresponds to a natural amplitude spike in the detectedelectromagnetic field.

466. The method of any of embodiments 462 to 465, wherein each durationcomprises a plurality of coherent noise cycles.

467. The method of embodiment 466, wherein each duration comprises atime of about 30 seconds to about 10 minutes.

468. The method of any of embodiments 462 to 467, wherein a time betweenthe intervals comprises an uneven fraction of a coherent noise cycle.

469. The method of any of embodiments 462 to 468, wherein a time betweeneach of the plurality of intervals comprises a fraction of an irrationalnumber.

470. The method of any of embodiments 462 to 469, wherein a time betweeneach of the plurality of intervals comprises a fraction of □.

471. The method of any of embodiments 462 to 470, further comprising:applying a frequency filter to the first signal and the second signal.

472. The method of any of embodiments 462 to 471, further comprisingsquaring the first signal and the second signal before processing thefirst signal and the second signal.

473. The method of any of embodiments 462 to 472, further comprising:recording the detected electromagnetic field and the detected seismicsignal; using the recorded detected electromagnetic field to generatethe first signal; and using the recorded detected seismic signal togenerate the second signal.

474. In an embodiment, a method comprises: generating a detectedelectromagnetic field by detecting earth's electromagnetic field usingat least one electromagnetic field detector in the earth; generating adetected seismic signal by detecting a seismic wave related to theearth's electromagnetic field using a seismic sensor; generating adetected noise signal by detecting at least one background noisecomponent; filtering the detected electromagnetic field, the detectedseismic signal, or both using the detected noise signal to provide afiltered signal, wherein the filtered signal comprises the detectedelectromagnetic field, the detected seismic signal, or both having anincreased signal to noise ratio; and processing the filtered signal andthe detected electromagnetic field, the detected seismic signal, or bothto determine at least one property of the subsurface earth formation.

475. The method of embodiment 474, wherein the background noisecomponent comprises a background electromagnetic field.

476. The method of embodiment 475, wherein the detected noise signal isgenerated with an electromagnetic field detector on or above the surfaceof the earth.

477. The method of embodiment 475 or 476, wherein the detected noisesignal is generated by cross-correlating the signal from the at leastone electromagnetic field detector in the earth.

478. The method of any of embodiments 475 to 477, wherein the detectednoise signal is generated by an electromagnetic field detector capableof measuring at least one horizontal electromagnetic field component inthe earth.

479. The method of any of embodiments 475 to 478, wherein the detectednoise signal is generated with an electromagnetic field sensor on orabove a surface of the earth and distanced from the at least oneelectromagnetic field detector in the earth.

480. The method of embodiment 474, wherein the detected noise signalcomprises a background seismic signal at the surface of the earth.

481. The method of embodiment 480, wherein the detected noise signal isgenerated using a plurality of seismic sensors.

482. In an embodiment, a method comprises: generating a detectedelectromagnetic field by detecting earth's electromagnetic field usingat least one electromagnetic field detector; generating a detectedseismic signal by detecting a seismic wave related to the earth'selectromagnetic field using a seismic sensor; isolating at least onenonlinear seismic signal from the detected seismic signal; andprocessing the at least one nonlinear seismic signal and the detectedelectromagnetic field to determine at least one property of thesubsurface earth formation.

483. The method of embodiment 482, wherein isolating at least onenonlinear seismic signal comprises: identifying fundamental frequenciespresent in the detected electromagnetic field by cross-correlating thedetected electromagnetic field and the detected seismic signal; andidentifying the at least one nonlinear seismic signal by filtering thefundamental frequencies from the detected seismic signal.

484. The method of embodiment 482 or 483, wherein isolating at least onenonlinear seismic signal comprises at least partially rectifying thedetected seismic signal.

485. The method of embodiment 483, wherein filtering the fundamentalfrequencies comprises using a band-pass filter.

486. In an embodiment, a method comprises: generating a detectedelectromagnetic field by detecting earth's electromagnetic field usingat least one electromagnetic field detector; generating a detectedseismic signal by detecting a seismic wave related to the earth'selectromagnetic field using a seismic sensor; isolating at least onenonlinear electromagnetic field response from the detectedelectromagnetic field; and processing the at least one nonlinearelectromagnetic field and the detected seismic signal to determine atleast one property of the subsurface earth formation.

487. The method of embodiment 486, wherein isolating at least onenonlinear electromagnetic field response comprises: identifyingfundamental frequencies present in the detected electromagnetic field bycross-correlating the detected electromagnetic field and the detectedseismic signal; and identifying the at least one nonlinearelectromagnetic field response by filtering the fundamental frequenciesfrom the detected electromagnetic field.

488. The method of embodiment 486 or 487, wherein isolating at least onenonlinear seismic signal comprises: identifying fundamental frequenciespresent in the detected electromagnetic field by cross-correlating thedetected electromagnetic field and a detected distant electromagneticfield generated by a distant electromagnetic field detector located atleast 500 yards from the at least one electromagnetic field detector;and identifying the at least one nonlinear electromagnetic fieldresponse by filtering the fundamental frequencies from the detectedelectromagnetic field.

489. The method of any of embodiments 486 to 488, wherein isolating atleast one nonlinear seismic signal comprises: identifying fundamentalfrequencies present in the detected electromagnetic field bycross-correlating the detected electromagnetic field and a detectedatmospheric electromagnetic field generated by an atmosphericelectromagnetic field detector located on or above the surface of theearth; and identifying the at least one nonlinear electromagnetic fieldresponse by filtering the fundamental frequencies from the detectedelectromagnetic field.

490. In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: one or more sensors coupled to aprocessor that detect one or more signals generated within a subsurfaceearth formation due to a seismoelectric response or an electroseismicresponse in at least one porous subsurface earth formation containing atleast one fluid; and an analysis tool, that when executed on theprocessor, configures the processor to: receive the one or more signalsfrom the one or more sensors; process at least a portion of the one ormore signals to determine at least one property of the subsurface earthformation.

491. The system of embodiment 490, wherein the one or more sensorscomprise: a plurality of seismic sensors that detects a seismic signalrelated to earth's electromagnetic field and produce a first signalindicative of the detected seismic signal; an electromagnetic fielddetector that measures the earth's electromagnetic field and produces asecond signal indicative of the detected electromagnetic field; andwherein the analysis tool receives the first signal and the secondsignal and determines the at least one property of a subsurface earthformation.

492. The system of embodiment 491, wherein the plurality of seismicsensors are arranged in an array over a portion of the subsurface earthformation.

493. The system of embodiment 491 or 492, wherein the electromagneticfield detector is disposed within the surface of the earth below theplurality of seismic sensors.

494. The system of any of embodiments 491 to 493, wherein the distancebetween each of the plurality of seismic sensors is less than one halfof the wavelength of the surface waves at an expected surface wavefrequency.

495. The system of any of embodiments 491 to 494, further comprising aplurality of electromagnetic field detectors.

496. The system of any of embodiments 491 to 495, wherein the secondsignal comprises a vertical component of the earth's electromagneticfield.

497. The system of any of embodiments 491 to 496, wherein the secondsignal comprises at least one horizontal component of the earth'selectromagnetic field.

498. The system of any of embodiments 491 to 497, wherein the secondsignal is indicative of a time-varying electromagnetic field.

499. The system of any of embodiments 491 to 498, wherein theelectromagnetic field detector comprises a plurality of pairs of porouspot electrodes, wherein each pair of porous pot electrodes areelectrically coupled.

500. The system of embodiment 499, wherein the pairs of porous potelectrodes comprise at least one component selected from the groupconsisting of copper sulfate, silver chloride, cadmium chloride, mercurychloride, and lead chloride.

501. The system of any of embodiments 491 to 500, wherein theelectromagnetic field detector comprises a plurality of pairs ofconductive electrodes, wherein each pair of conductive electrodes areelectrically coupled.

502. The system of embodiment 501, wherein the plurality of conductiveelectrodes comprises at least one conductive material selected from thegroup consisting of: copper, stainless steel, aluminum, gold, galvanizedmetal, iron, lead, brass, graphite, steel, alloys thereof, and anycombination thereof.

503. The system of any of embodiments 491 to 502, wherein theelectromagnetic field detector comprises a conductive electrode coupledto a porous pot electrode.

504. The system of any of embodiments 491 to 503, wherein the pluralityof seismic sensors comprises at least one sensor selected from the groupconsisting of: a hydrophone, a single-component geophone, atwo-component geophone, a three-component geophone, a single-axisaccelerometer, a two-axis accelerometer, a three-axis accelerometer, andany combination thereof.

505. The system of any of embodiments 491 to 504, wherein the at leastone property of the subsurface earth formation comprises at least oneproperty selected from the group consisting of: an existence of thesubsurface earth formation containing at least one fluid, a depth of thesubsurface earth formation, a porosity, a fluid permeability, acomposition of at least one fluid within the subsurface earth formation,a spatial extent of the subsurface earth formation, an orientation ofthe boundaries of the subsurface earth formation, a resistivity, and anycombination thereof.

506. The system of any of embodiments 491 to 505, further comprising arecording apparatus configured to record the first signal and the secondsignal on a non-transitory media.

507. The system of embodiment 506, wherein the recording apparatuscomprises a digital or analog recording device.

508. The system of any of embodiments 491 to 507, wherein the at leastone fluid comprises at least one component selected from the groupconsisting of: an aqueous fluid, a hydrocarbon, a petroleum, carbondioxide, and any combination thereof.

509. The system of embodiment 508, wherein the aqueous fluid comprisesat least one of potable water, fresh water, or brine.

510. The system of any of embodiments 491 to 509, wherein at least oneof the plurality of seismic sensors is disposed on the surface of theearth or within a wellbore.

511. The system of any of embodiments 491 to 510, wherein at least oneof the plurality of seismic sensors is disposed within a wellbore.

512. The system of any of embodiments 491 to 511, wherein theelectromagnetic field detector comprises an antenna disposed on or abovethe surface of the earth.

513. The system of embodiment 512, wherein the antenna comprises atleast one antenna selected from the group consisting of: aparallel-plate capacitor antenna comprising two or more parallelconducting plates, a single-plate capacitor antenna comprising oneelectrode electrically coupled to the earth, a monopole antennacomprising a conducting element, a dipole antenna comprising twoconducting elements, a multi-pole antenna comprising a plurality ofconducting elements, a directional antenna comprising conductingelements arranged to augment a signal amplitude in a particulardirection, a coil antenna comprising one or more coils of wire, and anycombination thereof.

514. The system of embodiment 512, wherein the antenna comprises aconcentric electric dipole.

515. The system of any of embodiments 491 to 514, wherein the analysistool further configures the processor to: remove a direct current (DC)portion of the second signal.

516. The system of any of embodiments 491 to 515, wherein the analysistool further configures the processor to: decimate a data setrepresenting at least one of the first signal or second signal.

517. The system of any of embodiments 491 to 516, wherein the analysistool further configures the processor to: filter a noise component fromat least one of the first signal or second signal.

518. The system of any of embodiments 491 to 517, wherein the analysistool further configures the processor to: filter at least one of thefirst signal or second signal using a predetermined frequency bandwidth.

519. In an embodiment, a system for identifying hydrocarbons in asubterranean formation comprises: a memory comprising a non-transitorycomputer readable media; a processor; and an analysis tool, that whenexecuted on the processor, configures the processor to: receive one ormore signals from one or more sensors, wherein the one or more sensorsdetect one or more signals generated within a subsurface earth formationdue to a seismoelectric response or an electroseismic response in atleast one porous subsurface earth formation containing at least onefluid; and process at least a portion of the one or more signals todetermine at least one property of the subsurface earth formation.

520. The system of embodiment 519, wherein the one or more sensorscomprise a seismic sensor that detects a seismic signal related toearth's electromagnetic field and produce a first signal indicative ofthe detected seismic signal, and an electromagnetic field detector thatmeasures the earth's electromagnetic field and produces a second signalindicative of the detected electromagnetic field; and wherein theanalysis tool configures the processor to receive the first signal andthe second signal and determine the at least one property of asubsurface earth formation.

At least one embodiment is disclosed and variations, combinations,and/or modifications of the embodiment(s) and/or features of theembodiment(s) made by a person having ordinary skill in the art arewithin the scope of the disclosure. Alternative embodiments that resultfrom combining, integrating, and/or omitting features of theembodiment(s) are also within the scope of the disclosure. Wherenumerical ranges or limitations are expressly stated, such expressranges or limitations should be understood to include iterative rangesor limitations of like magnitude falling within the expressly statedranges or limitations (e.g., from about 1 to about 10 includes, 2, 3, 4,etc.; greater than 0.10 includes 0.11, 0.12, 0.13, etc.). For example,whenever a numerical range with a lower limit, R_(l), and an upperlimit, R_(u), is disclosed, any number falling within the range isspecifically disclosed. In particular, the following numbers within therange are specifically disclosed: R=R_(l)+k*(R_(u)−R_(l)), wherein k isa variable ranging from 1 percent to 100 percent with a 1 percentincrement, i.e., k is 1 percent, 2 percent, 3 percent, 4 percent, 5percent, . . . , 50 percent, 51 percent, 52 percent, . . . , 95 percent,96 percent, 97 percent, 98 percent, 99 percent, or 100 percent.Moreover, any numerical range defined by two R numbers as defined in theabove is also specifically disclosed. Use of the term “optionally” withrespect to any element of a claim means that the element is required, oralternatively, the element is not required, both alternatives beingwithin the scope of the claim. Use of broader terms such as comprises,includes, and having should be understood to provide support fornarrower terms such as consisting of, consisting essentially of, andcomprised substantially of. Accordingly, the scope of protection is notlimited by the description set out above but is defined by the claimsthat follow, that scope including all equivalents of the subject matterof the claims. Each and every claim is incorporated as furtherdisclosure into the specification and the claims are embodiment(s) ofthe present invention.

What is claimed is:
 1. A system for surveying, comprising: an array ofsensors configured to be disposed above a subsurface formation, eachsensor in the array configured to detect one or more signals generatedby a subsurface earth formation in response to a passive-sourceelectromagnetic signal, wherein the one or more signals are generated byan electroseismic seismoelectric conversion of the passive-sourceelectromagnetic signal; a processor operable to: receive the one or moresignals from the array of sensors; and utilize the one or more signalsto generate a model of the subsurface earth formation.
 2. The system ofclaim 1, wherein the one or more signals comprise one or more of anelectromagnetic signal and a seismic signal.
 3. The system of claim 1,wherein the model comprises a three-dimensional model of the subsurfaceearth formation.
 4. The system of claim 1, wherein the one or moresignals comprises a first plurality of signals taken at a first time anda second plurality of signals taken at one or more second times, and themodel comprises a four-dimensional model of the subsurface earthformation.
 5. The system of claim 1, wherein the processor is furtherconfigured to utilize the array at a plurality of times in order tomonitor depletion of a hydrocarbon reservoir.
 6. The system of claim 1,wherein the subsurface earth formation comprises a reservoir and the oneor more time-dependent properties comprises one or more changes to thereservoir caused by production of a fluid from the reservoir.
 7. Thesystem of claim 1, wherein the one or more signals comprise a firstplurality of signals and a second plurality of signals, and theprocessor is further operable to: utilize the first plurality of signalsand the second plurality of signals to determine one or moretime-dependent characteristics of the subsurface earth formation; andwherein the model generated by the processor includes the one or moretime-dependent characteristics of the subsurface earth formation.
 8. Thesystem of claim 1, wherein the one or more signals comprise a firstplurality of signals received at a first time and a second plurality ofsignals received at a second time, wherein the array of sensors islocated at a first location at the first time and at a second locationat the second time.
 9. A method for surveying, comprising: detecting, byan array of sensors configured to be disposed above a subsurfaceformation, one or more signals generated by a subsurface earth formationin response to a passive-source electromagnetic signal, wherein the oneor more signals are generated by an electroseismic or seismoelectricconversion of the passive-source electromagnetic signal; transmitting,by the array of sensors, the one or more signals to a processor, whereinthe processor is configured to receive the one or more signals from thearray of sensors and utilize the one or more signals to generate a modelof the subsurface earth formation.
 10. The method of claim 9, whereinthe one or more signals comprise one or more of an electromagneticsignal and a seismic signal.
 11. The method of claim 9, wherein themodel comprises a three-dimensional model of the subsurface earthformation.
 12. The method of claim 9, wherein the one or more signalscomprises a first plurality of signals taken at a first time and asecond plurality of signals taken at one or more second times, and themodel comprises a four-dimensional model of the subsurface earthformation.
 13. The method of claim 9, wherein the processor is furtherconfigured to utilize the array at a plurality of times in order tomonitor depletion of a hydrocarbon reservoir.
 14. The method of claim 9,wherein the subsurface earth formation comprises a reservoir and the oneor more time-dependent properties comprises one or more changes to thereservoir caused by production of a fluid from the reservoir.
 15. Themethod of claim 9, wherein the one or more signals comprise a firstplurality of signals and a second plurality of signals, and theprocessor is further configured to: utilize the first plurality ofsignals and the second plurality of signals to determine one or moretime-dependent characteristics of the subsurface earth formation; andwherein the model generated by the processor includes the one or moretime-dependent characteristics of the subsurface earth formation. 16.The system of claim 9, wherein the one or more signals comprise a firstplurality of signals received at a first time and a second plurality ofsignals received at a second time, wherein the array of sensors islocated at a first location at the first time and at a second locationat the second time.
 17. A method for surveying, comprising: receivingdata, from an array of sensors configured to be disposed above asubsurface formation, the data corresponding to one or more signalsgenerated by a subsurface earth formation in response to apassive-source electromagnetic signal, wherein the one or more signalsare generated by an electroseismic seismoelectric conversion of thepassive-source electromagnetic signal; and utilizing, by a processor,the one or more signals to generate a model of the subsurface earthformation.
 18. The method of claim 17, wherein the one or more signalscomprise one or more of an electromagnetic signal and a seismic signal.19. The method of claim 17, wherein the model comprises athree-dimensional model of the subsurface earth formation.
 20. Themethod of claim 17, wherein the one or more signals comprises a firstplurality of signals taken at a first time and a second plurality ofsignals taken at one or more second times, and the model comprises afour-dimensional model of the subsurface earth formation.
 21. The methodof claim 17, further comprising utilizing the array at a plurality oftimes in order to monitor depletion of a hydrocarbon reservoir.
 22. Themethod of claim 17, wherein the subsurface earth formation comprises areservoir and the one or more time-dependent properties comprises one ormore changes to the reservoir caused by production of a fluid from thereservoir.
 23. The method of claim 17, wherein the one or more signalscomprise a first plurality of signals and a second plurality of signals,and the method further comprises: utilizing the first plurality ofsignals and the second plurality of signals to determine one or moretime-dependent characteristics of the subsurface earth formation; andwherein the model generated includes the one or more time-dependentcharacteristics of the subsurface earth formation.
 24. The method ofclaim 1, wherein the one or more signals comprise a first plurality ofsignals received at a first time and a second plurality of signalsreceived at a second time, wherein the array of sensors is located at afirst location at the first time and at a second location at the secondtime.
 25. A system, comprising: at least one processor; a memory, thememory including instructions that, when executed, cause the at leastone processor to: receive data, from an array of sensors configured tobe disposed above a subsurface formation, the data corresponding to oneor more signals generated by a subsurface earth formation in response toa passive-source electromagnetic signal, wherein the one or more signalsare generated by an electroseismic or seismoelectric conversion of thepassive-source electromagnetic signal; and utilize the one or moresignals to generate a model of the subsurface earth formation.
 26. Thesystem of claim 25, wherein the one or more signals comprise one or moreof an electromagnetic signal and a seismic signal.
 27. The system ofclaim 25, wherein the model comprises a three-dimensional model of thesubsurface earth formation.
 28. The system of claim 25, wherein the oneor more signals comprises a first plurality of signals taken at a firsttime and a second plurality of signals taken at one or more secondtimes, and the model comprises a four-dimensional model of thesubsurface earth formation.
 29. The system of claim 25, wherein theinstructions further cause the processor to utilize the array at aplurality of times in order to monitor depletion of a hydrocarbonreservoir.
 30. The system of claim 25, wherein the subsurface earthformation comprises a reservoir and the one or more time-dependentproperties comprises one or more changes to the reservoir caused byproduction of a fluid from the reservoir.